Ultra-low loss nano-taper coupler for Silicon-on-Insulator ridge waveguide

DEFF Research Database (Denmark)

Pu, Minhao; Liu, Liu; Ou, Haiyan

2010-01-01

A nano-taper coupler is optimized specially for the transverse-magnetic mode for interfacing light between a silicon-on-insulator ridge waveguide and a single-mode fiber. An ultra-low coupling loss of ~0.36dB is achieved for the nano-taper coupler.......A nano-taper coupler is optimized specially for the transverse-magnetic mode for interfacing light between a silicon-on-insulator ridge waveguide and a single-mode fiber. An ultra-low coupling loss of ~0.36dB is achieved for the nano-taper coupler....

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.

The single-event effect evaluation technology for nano integrated circuits

International Nuclear Information System (INIS)

Zheng Hongchao; Zhao Yuanfu; Yue Suge; Fan Long; Du Shougang; Chen Maoxin; Yu Chunqing

2015-01-01

Single-event effects of nano scale integrated circuits are investigated. Evaluation methods for single-event transients, single-event upsets, and single-event functional interrupts in nano circuits are summarized and classified in detail. The difficulties in SEE testing are discussed as well as the development direction of test technology, with emphasis placed on the experimental evaluation of a nano circuit under heavy ion, proton, and laser irradiation. The conclusions in this paper are based on many years of testing at accelerator facilities and our present understanding of the mechanisms for SEEs, which have been well verified experimentally. (paper)

Atomic structure and thermal stability of interfaces between metallic glass and embedding nano-crystallites revealed by molecular dynamics simulations

Energy Technology Data Exchange (ETDEWEB)

Gao, X.Z.; Yang, G.Q.; Xu, B.; Qi, C.; Kong, L.T., E-mail: konglt@sjtu.edu.cn; Li, J.F.

2015-10-25

Molecular dynamics simulations were performed to investigate the atomic structure and thermal stability of interfaces formed between amorphous Cu{sub 50}Zr{sub 50} matrix and embedding B2 CuZr nano-crystallites. The interfaces are found to be rather abrupt, and their widths show negligible dependence on the nano-crystallite size. Local atomic configuration in the interfacial region is dominated by geometry characterized by Voronoi polyhedra <0,5,2,6> and <0,4,4,6>, and the contents of these polyhedra also exhibit apparent size dependence, which in turn results in an increasing trend in the interfacial energy against the nano-crystallite size. Annealing of the interface models at elevated temperatures will also enrich these characterizing polyhedra. While when the temperature is as high as the glass transition temperature of the matrix, growth of the nano-crystallites will be appreciable. The growth activation energy also shows size dependence, which is lower for larger nano-crystallites, suggesting that large nano-crystallites are prone to grow upon thermal disturbance. - Highlights: • Special clusters characterizing the local geometry are abundant in the interfaces. • Their content varies with the size of the embedding nano-crystallite. • In turn, size dependences in interfacial thermodynamics and kinetics are observed.

Ab initio study of 3C-SiC/M (M = Ti or Al) nano-hetero interfaces

International Nuclear Information System (INIS)

Tanaka, Shingo; Kohyama, Masanori

2003-01-01

Ab initio pseudopotential calculation of 3C-SiC(1 1 1)/Al nano-hetero interfaces have been performed and interface atom species dependence (IASD) and interface orientation dependence (IOD) of nano-hetero interfaces between 3C-SiC ((1 1 1) or (0 0 1) orientation) and metal (Ti or Al) have been studied systematically. Stable atomic configurations of the 3C-SiC(1 1 1)/Al interfaces are quite different from those of the 3C-SiC(1 1 1)/Ti interfaces. Two terminated, Si-terminated (Si-TERM) and C-terminated (C-TERM), 3C-SiC(1 1 1)/Al interfaces have covalent bonding nature. In 3C-SiC/M (M = Ti or Al) nano-hetero interfaces, the C-terminated interface has relative strong, covalent and ionic C-Ti or C-Al bonds as TiC or SiC while the Si-terminated interface has various type of bonding nature, relative weak Si-Ti or Si-Al bonds from metallic character at the (0 0 1) interface to covalent character at the (1 1 1) interface. Adhesive energy (AE) shows strong IASD and IOD. The AE of the C-terminated interface is larger than that of the Si-terminated one. In the C-terminated interface, the AE of the (1 1 1) interface is smaller than that of the (0 0 1) one while in the Si-terminated interface there exists opposite interrelation. Schottky barrier height (SBH) also shows strong IASD and IOD. The SBH of the C-terminated interface is smaller than that of the Si-terminated one. The C-terminated SiC/Al interfaces have extremely small SBHs. In comparison with some experimental SBH, the present result is reliable as the difference of SBH between the two terminated interfaces and qualitative properties

Design, Simulation and Characteristics Research of the Interface Circuit based on nano-polysilicon thin films pressure sensor

Science.gov (United States)

Zhao, Xiaosong; Zhao, Xiaofeng; Yin, Liang

2018-03-01

This paper presents a interface circuit for nano-polysilicon thin films pressure sensor. The interface circuit includes consist of instrument amplifier and Analog-to-Digital converter (ADC). The instrumentation amplifier with a high common mode rejection ratio (CMRR) is implemented by three stages current feedback structure. At the same time, in order to satisfy the high precision requirements of pressure sensor measure system, the 1/f noise corner of 26.5 mHz can be achieved through chopping technology at a noise density of 38.2 nV/sqrt(Hz).Ripple introduced by chopping technology adopt continuous ripple reduce circuit (RRL), which achieves the output ripple level is lower than noise. The ADC achieves 16 bits significant digit by adopting sigma-delta modulator with fourth-order single-bit structure and digital decimation filter, and finally achieves high precision integrated pressure sensor interface circuit.

Engineering the Surface/Interface Structures of Titanium Dioxide Micro and Nano Architectures towards Environmental and Electrochemical Applications

Directory of Open Access Journals (Sweden)

Xiaoliang Wang

2017-11-01

Full Text Available Titanium dioxide (TiO2 materials have been intensively studied in the past years because of many varied applications. This mini review article focuses on TiO2 micro and nano architectures with the prevalent crystal structures (anatase, rutile, brookite, and TiO2(B, and summarizes the major advances in the surface and interface engineering and applications in environmental and electrochemical applications. We analyze the advantages of surface/interface engineered TiO2 micro and nano structures, and present the principles and growth mechanisms of TiO2 nanostructures via different strategies, with an emphasis on rational control of the surface and interface structures. We further discuss the applications of TiO2 micro and nano architectures in photocatalysis, lithium/sodium ion batteries, and Li–S batteries. Throughout the discussion, the relationship between the device performance and the surface/interface structures of TiO2 micro and nano structures will be highlighted. Then, we discuss the phase transitions of TiO2 nanostructures and possible strategies of improving the phase stability. The review concludes with a perspective on the current challenges and future research directions.

GUI2QAD, Graphical Interface for QAD-CGPIC, Point Kernel for Shielding Calculations

International Nuclear Information System (INIS)

2001-01-01

1 - Description of program or function: GUI2QAD is an aid in preparation of input for the included QAD-CGPIC program, which is based on CCC-493/QAD-CGGP and PICTURE. QAD-CGPIC, which is included in this distribution, is a Fortran code for neutron and gamma-ray shielding calculations by the point kernel method. Provision is available to interactively view the geometry of the system. QAD-CG calculates fast-neutron and gamma-ray penetration through various shield configurations defined by combinatorial geometry specifications. The code can use the ANS-6.4.3 1990 buildup factor compilation (26 materials). 2 - Methods:The code QAD-CGPIC is based on point kernel method and has a provision to select either GP or Capo's build up factors. 3 - Restrictions on the complexity of the problem: Details on restrictions and limitations are available in the RSICC code manual CCC-493/QAD-CGGP. Because CCC-493 was obsoleted by CCC-645/QAD-CGGP-A, the CCC-493 documentation is not online but is included with this package. This package includes a Graphical User Interface to facilitate use

Protein-nanoparticle interactions the bio-nano interface

CERN Document Server

Rahman, Masoud; Tawil, Nancy; Yahia, L'Hocine; Mahmoudi, Morteza

2013-01-01

In recent years, the fabrication of nanomaterials and exploration of their properties have attracted the attention of various scientific disciplines such as biology, physics, chemistry, and engineering. Although nanoparticulate systems are of significant interest in various scientific and technological areas, there is little known about the safety of these nanoscale objects. It has now been established that the surfaces of nanoparticles are immediately covered by biomolecules (e.g. proteins, ions, and enzymes) upon their entrance into a biological medium. This interaction with the biological medium modulates the surface of the nanoparticles, conferring a “biological identity” to their surfaces (referred to as a “corona”), which determines the subsequent cellular/tissue responses. The new interface between the nanoparticles and the biological medium/proteins, called “bio-nano interface,” has been very rarely studied in detail to date, though the interest in this topic is rapidly growing. In this bo...

Debugging Nano-Bio Interfaces: Systematic Strategies to Accelerate Clinical Translation of Nanotechnologies.

Science.gov (United States)

Mahmoudi, Morteza

2018-03-17

Despite considerable efforts in the field of nanomedicine that have been made by researchers, funding agencies, entrepreneurs, and the media, fewer nanoparticle (NP) technologies than expected have made it to clinical trials. The wide gap between the efforts and effective clinical translation is, at least in part, due to multiple overlooked factors in both in vitro and in vivo environments, a poor understanding of the nano-bio interface, and misinterpretation of the data collected in vitro, all of which reduce the accuracy of predictions regarding the NPs' fate and safety in humans. To minimize this bench-to-clinic gap, which may accelerate successful clinical translation of NPs, this opinion paper aims to introduce strategies for systematic debugging of nano-bio interfaces in the current literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Monte-Carlo Simulation of Hydrogen Adsorption in Single-Wall Carbon Nano-Cones

Directory of Open Access Journals (Sweden)

Zohreh Ahadi

2011-01-01

Full Text Available The properties of hydrogen adsorption in single-walled carbon nano-cones are investigated in detail by Monte Carlo simulations. A great deal of our computational results show that the hydrogen storage capacity in single-walled carbon nano-cones is slightly smaller than the capacity of single-walled carbon nanotubes at any time at the same conditions. This indicates that the hydrogen storage capacity of single-walled carbon nano-cones is related to angles of carbon nano-cones. It seems that these type of nanotubes could not exceed the 2010 goal of 6 wt%, which is presented by the U.S. Department of Energy. In addition, these results are discussed in theory.

Transfer Kernel Common Spatial Patterns for Motor Imagery Brain-Computer Interface Classification

Science.gov (United States)

Dai, Mengxi; Liu, Shucong; Zhang, Pengju

2018-01-01

Motor-imagery-based brain-computer interfaces (BCIs) commonly use the common spatial pattern (CSP) as preprocessing step before classification. The CSP method is a supervised algorithm. Therefore a lot of time-consuming training data is needed to build the model. To address this issue, one promising approach is transfer learning, which generalizes a learning model can extract discriminative information from other subjects for target classification task. To this end, we propose a transfer kernel CSP (TKCSP) approach to learn a domain-invariant kernel by directly matching distributions of source subjects and target subjects. The dataset IVa of BCI Competition III is used to demonstrate the validity by our proposed methods. In the experiment, we compare the classification performance of the TKCSP against CSP, CSP for subject-to-subject transfer (CSP SJ-to-SJ), regularizing CSP (RCSP), stationary subspace CSP (ssCSP), multitask CSP (mtCSP), and the combined mtCSP and ssCSP (ss + mtCSP) method. The results indicate that the superior mean classification performance of TKCSP can achieve 81.14%, especially in case of source subjects with fewer number of training samples. Comprehensive experimental evidence on the dataset verifies the effectiveness and efficiency of the proposed TKCSP approach over several state-of-the-art methods. PMID:29743934

Single-cell intracellular nano-pH probes†

Science.gov (United States)

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2016-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution. PMID:27708772

Single-cell intracellular nano-pH probes.

Science.gov (United States)

Özel, Rıfat Emrah; Lohith, Akshar; Mak, Wai Han; Pourmand, Nader

2015-01-01

Within a large clonal population, such as cancerous tumor entities, cells are not identical, and the differences between intracellular pH levels of individual cells may be important indicators of heterogeneity that could be relevant in clinical practice, especially in personalized medicine. Therefore, the detection of the intracellular pH at the single-cell level is of great importance to identify and study outlier cells. However, quantitative and real-time measurements of the intracellular pH of individual cells within a cell population is challenging with existing technologies, and there is a need to engineer new methodologies. In this paper, we discuss the use of nanopipette technology to overcome the limitations of intracellular pH measurements at the single-cell level. We have developed a nano-pH probe through physisorption of chitosan onto hydroxylated quartz nanopipettes with extremely small pore sizes (~100 nm). The dynamic pH range of the nano-pH probe was from 2.6 to 10.7 with a sensitivity of 0.09 units. We have performed single-cell intracellular pH measurements using non-cancerous and cancerous cell lines, including human fibroblasts, HeLa, MDA-MB-231 and MCF-7, with the pH nanoprobe. We have further demonstrated the real-time continuous single-cell pH measurement capability of the sensor, showing the cellular pH response to pharmaceutical manipulations. These findings suggest that the chitosan-functionalized nanopore is a powerful nano-tool for pH sensing at the single-cell level with high temporal and spatial resolution.

Nano-manipulation of single DNA molecules

International Nuclear Information System (INIS)

Hu Jun; Shanghai Jiaotong Univ., Shanghai; Lv Junhong; Wang Guohua; Wang Ying; Li Minqian; Zhang Yi; Li Bin; Li Haikuo; An Hongjie

2004-01-01

Nano-manipulation of single atoms and molecules is a critical technique in nanoscience and nanotechnology. This review paper will focus on the recent development of the manipulation of single DNA molecules based on atomic force microscopy (AFM). Precise manipulation has been realized including varied manipulating modes such as 'cutting', 'pushing', 'folding', 'kneading', 'picking up', 'dipping', etc. The cutting accuracy is dominated by the size of the AFM tip, which is usually 10 nm or less. Single DNA fragments can be cut and picked up and then amplified by single molecule PCR. Thus positioning isolation and sequencing can be performed. (authors)

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

Comparison of tungsten carbide and stainless steel ball bearings for grinding single maize kernels in a reciprocating grinder

Science.gov (United States)

Reciprocating grinders can grind single maize kernels by shaking the kernel in a vial with a ball bearing. This process results in a grind quality that is not satisfactory for many experiments. Tungesten carbide ball bearings are nearly twice as dense as steel, so we compared their grinding performa...

Characterization and H2-O2 reactivity of noble nano-metal tailored single wall nano-carbons

International Nuclear Information System (INIS)

K Kaneko; T Itoh; E Bekyarova; H Kanoh; S Utsumi; H Tanaka; M Yudasaka; S Iijima; S Iijima

2005-01-01

Full text of publication follows: Single wall carbon nano-tube (SWNT) and single wall carbon nano-horn (SWNH) have nano-spaces in their particles and the nano-spaces become open by oxidation. In particular, SWNH forms a unique colloidal structure which has micropores and meso-pores between the SWNH particles. Although non-treated SWNH colloids have quasi-one dimensional nano-pores [1], oxidized SWNH colloids have both of interstitial and internal nano-pores [2-5]. SWNH colloids show excellent supercritical methane storage ability [6], molecular sieving effect [7], and unique hydrogen adsorption characteristic [8]. Selective adsorptivity of SWNH colloids for H 2 and D 2 due to uncertainty principle of those molecules was shown [9-10]. As SWNH has no metallic impurities, we can study the effect of tailoring of metallic nano-particles on the surface activities of SWNH [11]. We tailored Pd or Pt nano-particles on SWNH and SWNH oxidized at 823 K (ox-SWNH) using poly[(2-oxo-pyrrolidine-1-yl)ethylene]. The oxidation of SWNH donates nano-scale windows to the single wall. The tailored metal amount was determined by TG analysis. TEM showed uniform dispersion of nano-metal particles of 2-3 nm in the diameter on SWNH. The nitrogen adsorption amount of SWNH oxidized decreases by tailoring, indicating that nano-particles are attached to the nano-scale windows. The electronic states of tailored metals were characterized by X-ray photoelectron spectroscopy. The surface activities of Pd tailored SWNH and ox-SWNH were examined for the reaction of hydrogen and oxygen near room temperature. The catalytic reactivities of Pd tailored SWNH and ox-SWNH were 4 times greater than that of Pd-dispersed activated carbon. The temperature dependence of the surface activity will be discussed with the relevance to the tube porosity. References [1] T. Ohba et al, J. Phys. Chem. In press. [2] S. Utsumi et al, J. Phys. Chem. In press. [3] C.- Min Yang, et al. Adv. Mater. In press. [4]C.M. Yang, J

An active nano-supported interface designed from gold nanoparticles embedded on ionic liquid for depositing DNA

International Nuclear Information System (INIS)

Lu Liping; Kang Tianfang; Cheng Shuiyuan; Guo Xiurui

2009-01-01

The use of an active nano-interface designed from gold nanoparticles embedded on ionic liquid for DNA damage resulted from formalehyde (HCHO) is reported in this article. The active nano-interface was fabricated by depositing gold nanoparticles on the ionic liquid 1-butyl-3-methylimidazolium tetrafluroborate ([bmim][BF 4 ]). A glassy carbon electrode modified by this composite film was fabricated to immobilize DNA for probing into the damage resulted from HCHO. The modifying process was characterized by X-ray photoelectron spectroscopy, atomic force microscopy and electrochemistry involving electrochemical impedance spectroscopy. It was found that the modified film performs effectively in studying the DNA damage by electrocatalytic activity toward HCHO oxidation.

Engineering the Surface/Interface Structures of Titanium Dioxide Micro and Nano Architectures towards Environmental and Electrochemical Applications

DEFF Research Database (Denmark)

Wang, Xiaoliang; Zhao, Yanyan; Mølhave, Kristian

2017-01-01

advances in the surface and interface engineering and applications in environmental and electrochemical applications. We analyze the advantages of surface/interface engineered TiO₂ micro and nano structures, and present the principles and growth mechanisms of TiO₂ nanostructures via different strategies...

The effect of STDP temporal kernel structure on the learning dynamics of single excitatory and inhibitory synapses.

Directory of Open Access Journals (Sweden)

Yotam Luz

Full Text Available Spike-Timing Dependent Plasticity (STDP is characterized by a wide range of temporal kernels. However, much of the theoretical work has focused on a specific kernel - the "temporally asymmetric Hebbian" learning rules. Previous studies linked excitatory STDP to positive feedback that can account for the emergence of response selectivity. Inhibitory plasticity was associated with negative feedback that can balance the excitatory and inhibitory inputs. Here we study the possible computational role of the temporal structure of the STDP. We represent the STDP as a superposition of two processes: potentiation and depression. This allows us to model a wide range of experimentally observed STDP kernels, from Hebbian to anti-Hebbian, by varying a single parameter. We investigate STDP dynamics of a single excitatory or inhibitory synapse in purely feed-forward architecture. We derive a mean-field-Fokker-Planck dynamics for the synaptic weight and analyze the effect of STDP structure on the fixed points of the mean field dynamics. We find a phase transition along the Hebbian to anti-Hebbian parameter from a phase that is characterized by a unimodal distribution of the synaptic weight, in which the STDP dynamics is governed by negative feedback, to a phase with positive feedback characterized by a bimodal distribution. The critical point of this transition depends on general properties of the STDP dynamics and not on the fine details. Namely, the dynamics is affected by the pre-post correlations only via a single number that quantifies its overlap with the STDP kernel. We find that by manipulating the STDP temporal kernel, negative feedback can be induced in excitatory synapses and positive feedback in inhibitory. Moreover, there is an exact symmetry between inhibitory and excitatory plasticity, i.e., for every STDP rule of inhibitory synapse there exists an STDP rule for excitatory synapse, such that their dynamics is identical.

Nano-imaging of single cells using STIM

Energy Technology Data Exchange (ETDEWEB)

Ren Minqin [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Department of Biochemistry, National University of Singapore (Singapore); Kan, J.A. van [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Bettiol, A.A. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Daina, Lim [Department of Anatomy, National University of Singapore (Singapore); Gek, Chan Yee [Department of Anatomy, National University of Singapore (Singapore); Huat, Bay Boon [Department of Anatomy, National University of Singapore (Singapore); Whitlow, H.J. [Department of Physics, University of Jyvaskyla, P.O. Box 35 (YFL), FIN-40014 (Finland); Osipowicz, T. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore); Watt, F. [Centre for Ion Beam Applications (CIBA), Department of Physics, National University of Singapore, Singapore 117542 (Singapore)]. E-mail: phywattf@nus.edu.sg

2007-07-15

Scanning transmission ion microscopy (STIM) is a technique which utilizes the energy loss of high energy (MeV) ions passing through a sample to provide structural images. In this paper, we have successfully demonstrated STIM imaging of single cells at the nano-level using the high resolution capability of the proton beam writing facility at the Centre for Ion Beam Applications, National University of Singapore. MCF-7 breast cancer cells (American Type Culture Collection [ATCC]) were seeded on to silicon nitride windows, backed by a Hamamatsu pin diode acting as a particle detector. A reasonable contrast was obtained using 1 MeV protons and excellent contrast obtained using 1 MeV alpha particles. In a further experiment, nano-STIM was also demonstrated using cells seeded on to the pin diode directly, and high quality nano-STIM images showing the nucleus and multiple nucleoli were extracted before the detector was significantly damaged.

Linear and ultrafast nonlinear plasmonics of single nano-objects

Science.gov (United States)

Crut, Aurélien; Maioli, Paolo; Vallée, Fabrice; Del Fatti, Natalia

2017-03-01

Single-particle optical investigations have greatly improved our understanding of the fundamental properties of nano-objects, avoiding the spurious inhomogeneous effects that affect ensemble experiments. Correlation with high-resolution imaging techniques providing morphological information (e.g. electron microscopy) allows a quantitative interpretation of the optical measurements by means of analytical models and numerical simulations. In this topical review, we first briefly recall the principles underlying some of the most commonly used single-particle optical techniques: near-field, dark-field, spatial modulation and photothermal microscopies/spectroscopies. We then focus on the quantitative investigation of the surface plasmon resonance (SPR) of metallic nano-objects using linear and ultrafast optical techniques. While measured SPR positions and spectral areas are found in good agreement with predictions based on Maxwell’s equations, SPR widths are strongly influenced by quantum confinement (or, from a classical standpoint, surface-induced electron scattering) and, for small nano-objects, cannot be reproduced using the dielectric functions of bulk materials. Linear measurements on single nano-objects (silver nanospheres and gold nanorods) allow a quantification of the size and geometry dependences of these effects in confined metals. Addressing the ultrafast response of an individual nano-object is also a powerful tool to elucidate the physical mechanisms at the origin of their optical nonlinearities, and their electronic, vibrational and thermal relaxation processes. Experimental investigations of the dynamical response of gold nanorods are shown to be quantitatively modeled in terms of modifications of the metal dielectric function enhanced by plasmonic effects. Ultrafast spectroscopy can also be exploited to unveil hidden physical properties of more complex nanosystems. In this context, two-color femtosecond pump-probe experiments performed on individual

Modeling of cross-plane interface thermal conductance between graphene nano-ribbons

International Nuclear Information System (INIS)

Varshney, Vikas; Lee, Jonghoon; Farmer, Barry L; Voevodin, Andrey A; Roy, Ajit K

2014-01-01

Using non-equilibrium molecular dynamics for thermal energy transfer, we investigate the interfacial thermal conductance between non-covalently interacting graphene nano-ribbons (GNRs) of varying lengths and widths in a cross-contact (x-shaped) geometry. Our results show that the out-of-plane conductance between GNRs can vary significantly (up to a factor of 4) depending upon their geometric parameters. We observe that when plotted against aspect ratio, the predicted interface thermal conductance values fit excellently on a single master-plot with a logarithmic scaling, suggesting the importance of GNR aspect ratio towards thermal conductance. We propose a model based on incorporating different thermal conductance characteristics of edge and inner interacting regions which predicts the observed logarithmic dependence on aspect ratio. We also study the effect of graphene edge roughness, temperature, and strain on out-of-plane thermal conductance and discuss the observed results based on local vibrational characteristics of atoms within interacting region, number of interacting phonons, and the degree to which they interact across the interaction zone. (paper)

Managing collaboration in the nanoManipulator

DEFF Research Database (Denmark)

Hudson, Thomas C.; Heiser, Aron T.; Sonnenwald, Diane H.

2003-01-01

We designed, developed, deployed, and evaluated the Collaborative nanoManipulator (CnM), a system supporting remote collaboration between users of the nanoManipulator interface to atomic force microscopes. To be accepted by users, the shared nanoManipulator application had to have the same high...... level of interactivity as the single user system and the application had to support a user's ability to interleave working privately and working collaboratively. This paper briefly describes the entire collaboration system, but focuses on the shared nanoManipulator application. Based on our experience...... developing the CnM, we present: a method of analyzing applications to characterize the requirements for sharing data between collaborating sites, examples of data structures that support collaboration, and guidelines for selecting appropriate synchronization and concurrency control schemes....

Nano-scale Materials and Nano-technology Processes in Environmental Protection

International Nuclear Information System (INIS)

Vissokov, Gh; Tzvetkoff, T.

2003-01-01

A number of environmental and energy technologies have benefited substantially from nano-scale technology: reduced waste and improved energy efficiency; environmentally friendly composite structures; waste remediation; energy conversion. In this report examples of current achievements and paradigm shifts are presented: from discovery to application; a nano structured materials; nanoparticles in the environment (plasma chemical preparation); nano-porous polymers and their applications in water purification; photo catalytic fluid purification; hierarchical self-assembled nano-structures for adsorption of heavy metals, etc. Several themes should be considered priorities in developing nano-scale processes related to environmental management: 1. To develop understanding and control of relevant processes, including protein precipitation and crystallisation, desorption of pollutants, stability of colloidal dispersion, micelle aggregation, microbe mobility, formation and mobility of nanoparticles, and tissue-nanoparticle interaction. Emphasis should be given to processes at phase boundaries (solid-liquid, solid-gas, liquid-gas) that involve mineral and organic soil components, aerosols, biomolecules (cells, microbes), bio tissues, derived components such as bio films and membranes, and anthropogenic additions (e.g. trace and heavy metals); 2. To carry out interdisciplinary research that initiates Noel approaches and adopts new methods for characterising surfaces and modelling complex systems to problems at interfaces and other nano-structures in the natural environment, including those involving biological or living systems. New technological advances such as optical traps, laser tweezers, and synchrotrons are extending examination of molecular and nano-scale processes to the single-molecule or single-cell level; 3. To integrate understanding of the roles of molecular and nano-scale phenomena and behaviour at the meso- and/or macro-scale over a period of time

Nano-LED array fabrication suitable for future single photon lithography

International Nuclear Information System (INIS)

Mikulics, M; Hardtdegen, H

2015-01-01

We report on an alternative illumination concept for a future lithography based on single-photon emitters and important technological steps towards its implementation. Nano light-emitting diodes (LEDs) are chosen as the photon emitters. First, the development of their fabrication and their integration technology is presented, then their optical characteristics assessed. Last, size-controlled nano-LEDs, well positioned in an array, are electrically driven and utilized for illumination. Nanostructures are lithographically formed, demonstrating the feasibility of the approach. The potential of single-photon lithography to reach the ultimate scale limits in mass production is discussed. (paper)

Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers.

Science.gov (United States)

Mogensen, J M; Sørensen, S M; Sulyok, M; van der Westhuizen, L; Shephard, G S; Frisvad, J C; Thrane, U; Krska, R; Nielsen, K F

2011-12-01

Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n=15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins. The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin content by 71%. Of the 400 kernels, 80 were screened for 186 microbial metabolites by liquid chromatography-tandem mass spectrometry, detecting 17 other fungal metabolites, including fusaric acid, equisetin, fusaproliferin, beauvericin, cyclosporins, agroclavine, chanoclavine, rugulosin and emodin. Fusaric acid in samples without fumonisins indicated the possibility of using non-toxinogenic Fusaria as biocontrol agents to reduce fumonisin exposure, as done for Aspergillus flavus. This is the first report of mycotoxin profiling in single naturally infected maize kernels. © 2011 Taylor & Francis

Evaluation of the Single-precision Floatingpoint Vector Add Kernel Using the Intel FPGA SDK for OpenCL

Energy Technology Data Exchange (ETDEWEB)

Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-04-20

Open Computing Language (OpenCL) is a high-level language that enables software programmers to explore Field Programmable Gate Arrays (FPGAs) for application acceleration. The Intel FPGA software development kit (SDK) for OpenCL allows a user to specify applications at a high level and explore the performance of low-level hardware acceleration. In this report, we present the FPGA performance and power consumption results of the single-precision floating-point vector add OpenCL kernel using the Intel FPGA SDK for OpenCL on the Nallatech 385A FPGA board. The board features an Arria 10 FPGA. We evaluate the FPGA implementations using the compute unit duplication and kernel vectorization optimization techniques. On the Nallatech 385A FPGA board, the maximum compute kernel bandwidth we achieve is 25.8 GB/s, approximately 76% of the peak memory bandwidth. The power consumption of the FPGA device when running the kernels ranges from 29W to 42W.

Superconducting nano-striplines as quantum detectors

International Nuclear Information System (INIS)

Casaburi, A.; Ejrnaes, M.; Mattioli, F.; Gaggero, A.; Leoni, R.; Martucciello, N.; Pagano, S.; Ohkubo, M.; Cristiano, R.

2011-01-01

The recent progress in the nanofabrication of superconducting films opens the road toward detectors with highly improved performances. This is the case for superconducting nano-striplines where the thickness and the width are pushed down to the extreme limits to realize detectors with unprecedented sensitivity and ultra fast response time. In this way quantum detectors for single photons at telecommunication wavelengths and for macromolecules such as proteins can be realized. As is often the case in applied nanotechnology, it is a challenge to make devices with the necessary macroscopic dimensions that are needed to interface present technologies, while maintaining the performance improvements. For nano-stripline detectors, both the fast temporal response and the device sensitivity is generally degraded when the area is increased. Here, we present how such detectors can be scaled up to macroscopic dimensions without losing the performance of the nano-structured active elements by using an innovative configuration. In order to realize ultrathin superconducting film the nano-layer is growth with a careful setup of the deposition technique which guarantees high quality and thickness uniformity at the nano-scale size. The active nano-strips are defined with the state-of-the-art electron beam nanolithography to achieve a highly uniform linewidth. We present working detectors based on nano-strips with thicknesses 9–40 nm and widths of 100–1000 nm which exhibit unprecedented speed and area coverage (40 × 40 μm 2 for single photon detectors and 1 × 1 mm 2 for single molecule detectors) based on niobium nitride thus enabling practical use of this nanotechnology.

Giant piezoresistance of p-type nano-thick silicon induced by interface electron trapping instead of 2D quantum confinement

International Nuclear Information System (INIS)

Yang Yongliang; Li Xinxin

2011-01-01

The p-type silicon giant piezoresistive coefficient is measured in top-down fabricated nano-thickness single-crystalline-silicon strain-gauge resistors with a macro-cantilever bending experiment. For relatively thicker samples, the variation of piezoresistive coefficient in terms of silicon thickness obeys the reported 2D quantum confinement effect. For ultra-thin samples, however, the variation deviates from the quantum-effect prediction but increases the value by at least one order of magnitude (compared to the conventional piezoresistance of bulk silicon) and the value can change its sign (e.g. from positive to negative). A stress-enhanced Si/SiO 2 interface electron-trapping effect model is proposed to explain the 'abnormal' giant piezoresistance that should be originated from the carrier-concentration change effect instead of the conventional equivalent mobility change effect for bulk silicon piezoresistors. An interface state modification experiment gives preliminary proof of our analysis.

Nano-modified adhesive by graphene: the single lap-joint case

Energy Technology Data Exchange (ETDEWEB)

Silva Neto, Almir; Cruz, Diego Thadeu Lopes da; Avila, Antonio Ferreira, E-mail: aavila@netuno.lcc.ufmg.b [Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG (Brazil). Dept. de Engenharia Mecanica

2013-11-01

This paper addresses the performance study on, low viscosity, nano-modified adhesives by graphene. For achieving this goal, single-lap joints following ASTM D 5868-01 were manufactured and tested. X-ray diffraction, scanning electron microscopy and nanoindentation were employed for graphene based nanostructures characterization. The increase on joint strength was around 57% when compared against the control group. Furthermore, all failures for the nano-modified adhesive were cohesive failure for the carbon fibre/epoxy composites indicating that the adhesive was tested. X-ray diffractions signatures indicate formation of nano-structures with 17-19 nm diameters. Moreover, nanoindentation tests revealed a homogeneous dispersion of graphene. (author)

Seawater Durability of Nano-Montmorillonite Modified Single-Lap Joining Epoxy Composite Laminates

OpenAIRE

ULUS, Hasan; KAYBAL, Halil Burak; DEMİR, Okan; TATAR, Ahmet Caner; SENYURT, Muhammed Ali; AVCI, Ahmet

2018-01-01

The objective of this study was to investigate of nano-montmorillonite modified epoxy composite single-lap bonded joints, after being exposed to seawater immersion in order to understand the effect of seawater environment on their performance. To prepare the nano adhesives, nano montmorillonite (2 wt %) was incorporated into epoxy resin. Composite bonded specimens which manufactured with VARIM (Vacuum Assisted Resin Infusion Method) were prepared accordance with ASTM D5868-01 and immersed in ...

Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications

Science.gov (United States)

Hekmatmanesh, Amin; Jamaloo, Fatemeh; Wu, Huapeng; Handroos, Heikki; Kilpeläinen, Asko

2018-04-01

Brain Computer Interface (BCI) can be a challenge for developing of robotic, prosthesis and human-controlled systems. This work focuses on the implementation of a common spatial pattern (CSP) base algorithm to detect event related desynchronization patterns. Utilizing famous previous work in this area, features are extracted by filter bank with common spatial pattern (FBCSP) method, and then weighted by a sensitive learning vector quantization (SLVQ) algorithm. In the current work, application of the radial basis function (RBF) as a mapping kernel of linear discriminant analysis (KLDA) method on the weighted features, allows the transfer of data into a higher dimension for more discriminated data scattering by RBF kernel. Afterwards, support vector machine (SVM) with generalized radial basis function (GRBF) kernel is employed to improve the efficiency and robustness of the classification. Averagely, 89.60% accuracy and 74.19% robustness are achieved. BCI Competition III, Iva data set is used to evaluate the algorithm for detecting right hand and foot imagery movement patterns. Results show that combination of KLDA with SVM-GRBF classifier makes 8.9% and 14.19% improvements in accuracy and robustness, respectively. For all the subjects, it is concluded that mapping the CSP features into a higher dimension by RBF and utilization GRBF as a kernel of SVM, improve the accuracy and reliability of the proposed method.

METHOD FOR MANUFACTURING A SINGLE CRYSTAL NANO-WIRE

NARCIS (Netherlands)

Van Den Berg, Albert; Bomer, Johan; Carlen Edwin, Thomas; Chen, Songyue; Kraaijenhagen Roderik, Adriaan; Pinedo Herbert, Michael

2012-01-01

A method for manufacturing a single crystal nano-structure includes providing a device layer with a 100 structure on a substrate; providing a stress layer onto the device layer; patterning the stress layer along the 110 direction of the device layer; selectively removing parts of the stress layer to

METHOD FOR MANUFACTURING A SINGLE CRYSTAL NANO-WIRE.

NARCIS (Netherlands)

Van Den Berg, Albert; Bomer, Johan; Carlen Edwin, Thomas; Chen, Songyue; Kraaijenhagen Roderik, Adriaan; Pinedo Herbert, Michael

2011-01-01

A method for manufacturing a single crystal nano-structure is provided comprising the steps of providing a device layer with a 100 structure on a substrate; providing a stress layer onto the device layer; patterning the stress layer along the 110 direction of the device layer; selectively removing

Nano- and microparticles at fluid and biological interfaces

Science.gov (United States)

Dasgupta, S.; Auth, T.; Gompper, G.

2017-09-01

Systems with interfaces are abundant in both technological applications and biology. While a fluid interface separates two fluids, membranes separate the inside of vesicles from the outside, the interior of biological cells from the environment, and compartmentalize cells into organelles. The physical properties of interfaces are characterized by interface tension, those of membranes are characterized by bending and stretching elasticity. Amphiphilic molecules like surfactants that are added to a system with two immiscible fluids decrease the interface tension and induce a bending rigidity. Lipid bilayer membranes of vesicles can be stretched or compressed by osmotic pressure; in biological cells, also the presence of a cytoskeleton can induce membrane tension. If the thickness of the interface or the membrane is small compared with its lateral extension, both can be described using two-dimensional mathematical surfaces embedded in three-dimensional space. We review recent work on the interaction of particles with interfaces and membranes. This can be micrometer-sized particles at interfaces that stabilise emulsions or form colloidosomes, as well as typically nanometer-sized particles at membranes, such as viruses, parasites, and engineered drug delivery systems. In both cases, we first discuss the interaction of single particles with interfaces and membranes, e.g. particles in external fields, non-spherical particles, and particles at curved interfaces, followed by interface-mediated interaction between two particles, many-particle interactions, interface and membrane curvature-induced phenomena, and applications.

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...

Single pass kernel k-means clustering method

Indian Academy of Sciences (India)

In unsupervised classification, kernel -means clustering method has been shown to perform better than conventional -means clustering method in ... 518501, India; Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Anantapur College of Engineering, Anantapur 515002, India ...

Kernel PLS Estimation of Single-trial Event-related Potentials

Science.gov (United States)

Rosipal, Roman; Trejo, Leonard J.

2004-01-01

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

A versatile nanotechnology to connect individual nano-objects for the fabrication of hybrid single-electron devices

International Nuclear Information System (INIS)

Bernand-Mantel, A; Bouzehouane, K; Seneor, P; Fusil, S; Deranlot, C; Petroff, F; Fert, A; Brenac, A; Notin, L; Morel, R

2010-01-01

We report on the high yield connection of single nano-objects as small as a few nanometres in diameter to separately elaborated metallic electrodes, using a 'table-top' nanotechnology. Single-electron transport measurements validate that transport occurs through a single nano-object. The vertical geometry of the device natively allows an independent choice of materials for each electrode and the nano-object. In addition ferromagnetic materials can be used without encountering oxidation problems. The possibility of elaborating such hybrid nanodevices opens new routes for the democratization of spintronic studies in low dimensions.

Nano features of Al/Au ultrasonic bond interface observed by high resolution transmission electron microscopy

International Nuclear Information System (INIS)

Ji Hongjun; Li Mingyu; Kim, Jong-Myung; Kim, Dae-Won; Wang Chunqing

2008-01-01

Nano-scale interfacial details of ultrasonic AlSi1 wire wedge bonding to a Au/Ni/Cu pad were investigated using high resolution transmission electron microscopy (HRTEM). The intermetallic phase Au 8 Al 3 formed locally due to diffusion and reaction activated by ultrasound at the Al/Au bond interface. Multilayer sub-interfaces roughly parallel to the wire/pad interface were observed among this phase, and interdiffusional features near the Au pad resembled interference patterns, alternately dark and bright bars. Solid-state diffusion theory cannot be used to explain why such a thick compound formed within milliseconds at room temperature. The major formation of metallurgical bonds was attributed to ultrasonic cyclic vibration

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

Control of cancer growth using single input autonomous fuzzy Nano-particles

Directory of Open Access Journals (Sweden)

Fahimeh Razmi

2015-04-01

Full Text Available In this paper a single input fuzzy controller is applied on autonomous drug-encapsulated nanoparticles (ADENPs to restrict the cancer growth. The proposed ADENPs, swarmly release the drug in local cancerous tissue and effectively decreases the destruction of normal tissue. The amount of released drug is defined considering to feed backed values of tumor growth rate and the used drug. Some significant characteristics of Nano particles compared to Nano-robots is their ability to recognize the cancerous tissue from the normal one and their simple structure. Nano particles became an attractive topic in Nano science and many efforts have been done to manufacture these particles. Simulation results show that the proposed controlling method not only decreases the cancerous tissue effectively but also reduces the side effects of drug impressively.

An obstructive sleep apnea detection approach using kernel density classification based on single-lead electrocardiogram.

Science.gov (United States)

Chen, Lili; Zhang, Xi; Wang, Hui

2015-05-01

Obstructive sleep apnea (OSA) is a common sleep disorder that often remains undiagnosed, leading to an increased risk of developing cardiovascular diseases. Polysomnogram (PSG) is currently used as a golden standard for screening OSA. However, because it is time consuming, expensive and causes discomfort, alternative techniques based on a reduced set of physiological signals are proposed to solve this problem. This study proposes a convenient non-parametric kernel density-based approach for detection of OSA using single-lead electrocardiogram (ECG) recordings. Selected physiologically interpretable features are extracted from segmented RR intervals, which are obtained from ECG signals. These features are fed into the kernel density classifier to detect apnea event and bandwidths for density of each class (normal or apnea) are automatically chosen through an iterative bandwidth selection algorithm. To validate the proposed approach, RR intervals are extracted from ECG signals of 35 subjects obtained from a sleep apnea database ( http://physionet.org/cgi-bin/atm/ATM ). The results indicate that the kernel density classifier, with two features for apnea event detection, achieves a mean accuracy of 82.07 %, with mean sensitivity of 83.23 % and mean specificity of 80.24 %. Compared with other existing methods, the proposed kernel density approach achieves a comparably good performance but by using fewer features without significantly losing discriminant power, which indicates that it could be widely used for home-based screening or diagnosis of OSA.

Electron scattering at interfaces in nano-scale vertical interconnects: A combined experimental and ab initio study

Science.gov (United States)

Lanzillo, Nicholas A.; Restrepo, Oscar D.; Bhosale, Prasad S.; Cruz-Silva, Eduardo; Yang, Chih-Chao; Youp Kim, Byoung; Spooner, Terry; Standaert, Theodorus; Child, Craig; Bonilla, Griselda; Murali, Kota V. R. M.

2018-04-01

We present a combined theoretical and experimental study on the electron transport characteristics across several representative interface structures found in back-end-of-line interconnect stacks for advanced semiconductor manufacturing: Cu/Ta(N)/Co/Cu and Cu/Ta(N)/Ru/Cu. In particular, we evaluate the impact of replacing a thin TaN barrier with Ta while considering both Co and Ru as wetting layers. Both theory and experiment indicate a pronounced reduction in vertical resistance when replacing TaN with Ta, regardless of whether a Co or Ru wetting layer is used. This indicates that a significant portion of the total vertical resistance is determined by electron scattering at the Cu/Ta(N) interface. The electronic structure of these nano-sized interconnects is analyzed in terms of the atom-resolved projected density of states and k-resolved transmission spectra at the Fermi level. This work further develops a fundamental understanding of electron transport and material characteristics in nano-sized interconnects.

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)

Deliquescence behavior of photo-irradiated single NaNO3 droplets

Science.gov (United States)

Seng, Samantha; Guo, Fangqin; Tobon, Yeny A.; Ishikawa, Tomoki; Moreau, Myriam; Ishizaka, Shoji; Sobanska, Sophie

2018-06-01

Nitrate-containing particles are ubiquitous in the troposphere because of their secondary production due to anthropogenic emissions of NOx from the combustion of fossil fuels. Nitrate ions are recognized as photoactive species that may contribute to the formation of oxidants in the atmosphere through heterogeneous photochemical reactions. The chemical transformation of aerosol particles in the atmosphere often leads to modification of the particles' hygroscopic properties. Although the photo-transformation of nitrate ions into nitrite within aerosol particles has been investigated, the influence of the photoproducts formation on the hygroscopic behavior of particles has not been reported. In this study, we examined the hygroscopic properties of single, ultraviolet-irradiated NaNO3 droplets using Raman microspectrometry. We are the first demonstrated that irradiating NaNO3 particles affects their hygroscopic behavior. For short-term exposures, regarding hygroscopic behavior, the irradiated particles exhibited two-stage transitions that were clearly reproduced in the experimental NaNO3-NaNO2 phase diagram. The production of NO2- decreased the deliquescence relative humidity values. For long irradiation times (>5 h), these values are even more affected by the additional production of peroxynitrite and carbonate ions in individual droplets. The NaNO3-NaNO2 deliquescence phase diagram cannot explain the hygroscopic behavior of long-term irradiated particles. Finally, we demonstrated the influence that CO2 has on the photo-transformation process in NaNO3 droplets.

Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

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

Effect of microscopic structure on deformation in nano-sized copper and Cu/Si interfacial cracking

Energy Technology Data Exchange (ETDEWEB)

Sumigawa, Takashi, E-mail: sumigawa@cyber.kues.kyoto-u.ac.jp; Nakano, Takuya; Kitamura, Takayuki

2013-03-01

The purpose of this work is to examine the effect of microscopic structure on the mechanical properties of nano-sized components (nano-components). We developed a bending specimen with a substructure that can be observed by means of a transmission electron microscope (TEM). We examined the plastic behavior of a Cu bi-crystal and the Cu/Si interfacial cracking in a nano-component. TEM images indicated that an initial plastic deformation takes place near the interface edge (the junction between the Cu/Si interface and the surface) in the Cu film with a high critical resolved shear stress (400–420 MPa). The deformation developed preferentially in a single grain. Interfacial cracking took place at the intersection between the grain boundary and the Cu/Si interface, where a high stress concentration existed due to deformation mismatch. These results indicate that the characteristic mechanical behavior of a nano-component is governed by the microscopic stress field, which takes into account the crystallographic structure. - Highlights: ► A nano-component specimen including a bi-crystal copper layer was prepared. ► A loading test with in-situ transmission electron microscopy was conducted. ► The plastic and cracking behaviors were governed by microscopic stress. ► Stress defined under continuum assumption was still present in nano-components.

Enhanced piezoelectric properties of vertically aligned single-crystalline NKN nano-rod arrays.

Science.gov (United States)

Kang, Min-Gyu; Oh, Seung-Min; Jung, Woo-Suk; Moon, Hi Gyu; Baek, Seung-Hyub; Nahm, Sahn; Yoon, Seok-Jin; Kang, Chong-Yun

2015-05-08

Piezoelectric materials capable of converting between mechanical and electrical energy have a great range of potential applications in micro- and nano-scale smart devices; however, their performance tends to be greatly degraded when reduced to a thin film due to the large clamping force by the substrate and surrounding materials. Herein, we report an effective method for synthesizing isolated piezoelectric nano-materials as means to relax the clamping force and recover original piezoelectric properties of the materials. Using this, environmentally friendly single-crystalline NaxK1-xNbO3 (NKN) piezoelectric nano-rod arrays were successfully synthesized by conventional pulsed-laser deposition and demonstrated to have a remarkably enhanced piezoelectric performance. The shape of the nano-structure was also found to be easily manipulated by varying the energy conditions of the physical vapor. We anticipate that this work will provide a way to produce piezoelectric micro- and nano-devices suitable for practical application, and in doing so, open a new path for the development of complex metal-oxide nano-structures.

Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

Science.gov (United States)

Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

2013-02-01

This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

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.

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.

Exploring abiotic stress on asynchronous protein metabolism in single kernels of wheat studied by NMR spectroscopy and chemometrics

DEFF Research Database (Denmark)

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

2009-01-01

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

Nano-Satellite Secondary Spacecraft on Deep Space Missions

Science.gov (United States)

Klesh, Andrew T.; Castillo-Rogez, Julie C.

2012-01-01

NanoSat technology has opened Earth orbit to extremely low-cost science missions through a common interface that provides greater launch accessibility. They have also been used on interplanetary missions, but these missions have used one-off components and architectures so that the return on investment has been limited. A natural question is the role that CubeSat-derived NanoSats could play to increase the science return of deep space missions. We do not consider single instrument nano-satellites as likely to complete entire Discovery-class missions alone,but believe that nano-satellites could augment larger missions to significantly increase science return. The key advantages offered by these mini-spacecrafts over previous planetary probes is the common availability of advanced subsystems that open the door to a large variety of science experiments, including new guidance, navigation and control capabilities. In this paper, multiple NanoSat science applications are investigated, primarily for high risk/high return science areas. We also address the significant challenges and questions that remain as obstacles to the use of nano-satellites in deep space missions. Finally, we provide some thoughts on a development roadmap toward interplanetary usage of NanoSpacecraft.

Nano-Reinforcement of Interfaces in Prepreg-Based Composites Using a Carbon Nanotubes Spraying Method

KAUST Repository

Almuhammadi, Khaled

2012-11-01

Multi-scale reinforcement of composite materials is a topic a great interest owing to the several advantages provided, e.g. increased stiffness, improved aging resistance, and fracture toughness. It is well known, that the fracture toughness of epoxy resins used as matrix materials for CFRP composites can be increased by the addition of nano-sized fillers such as Carbon nanotubes (CNTs). CNTs are particularly well suited for this purpose because of their nano-scale diameter and high aspect ratio which allow enhancing the contact area and adhesion to the epoxy matrix. On the other hand, CNTs can also be used to improve the interlaminar strength of composite, which is the resistance offered to delamination. Several fabrication techniques have been devised to this purpose, such as powder dispersion [51-53], spraying [54], roll coating [2] and electrospinning [55, 56]. The aim of this work is to extend the knowledge in this field. In particular, MWCNTs were dispersed throughout the interface of a carbon fiber composite laminate ([0o]16) through spraying and the resulting fracture toughness was investigated in detail. To this purpose, Double Cantilever Beam (DCB) specimens were fabricated by placing 0.5 wt.% CNTs at the interface of mid-plane plies and the fracture toughness was determined using the ASTM standard procedures. For comparison, baseline samples were prepared using neat prepregs. In order to corroborate the variation of fracture toughness to the modifications of interfacial damage mechanisms, Scanning Electron Microscopy (SEM) of the failed surfaces was also undertaken. The results of this work have shown that functionalized MWCNTs can enhance the interlaminar fracture toughness; indeed, compared to the neat case, an average increase around 17% was observed. The SEM analysis revealed that the improved fracture toughness was related to the ability of the Nano-reinforcement to spread the damage through crack bridging, i.e. CNTs pull-out and peeling.

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 atomic hydrogen adsorption on single-walled carbon nano tubes properties

International Nuclear Information System (INIS)

Jalili, S.; Majidi, R.

2007-01-01

We investigated the adsorption of hydrogen atoms on metallic single-walled carbon nano tubes using ab initio molecular dynamics method. It was found that the geometric structures and the electronic properties of hydrogenated SWNTs can be strongly changed by varying hydrogen coverage. The circular cross sections of the CNTs were changed with different hydrogen coverage. When hydrogen is chemisorbed on the surface of the carbon nano tube, the energy gap will be appeared. This is due to the degree of the Sp 3 hybridization, and the hydrogen coverage can control the band gap of the carbon nano tube

Learning a peptide-protein binding affinity predictor with kernel ridge regression

Science.gov (United States)

2013-01-01

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

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

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...

Development of Point Kernel Shielding Analysis Computer Program Implementing Recent Nuclear Data and Graphic User Interfaces

International Nuclear Information System (INIS)

Kang, Sang Ho; Lee, Seung Gi; Chung, Chan Young; Lee, Choon Sik; Lee, Jai Ki

2001-01-01

In order to comply with revised national regulationson radiological protection and to implement recent nuclear data and dose conversion factors, KOPEC developed a new point kernel gamma and beta ray shielding analysis computer program. This new code, named VisualShield, adopted mass attenuation coefficient and buildup factors from recent ANSI/ANS standards and flux-to-dose conversion factors from the International Commission on Radiological Protection (ICRP) Publication 74 for estimation of effective/equivalent dose recommended in ICRP 60. VisualShield utilizes graphical user interfaces and 3-D visualization of the geometric configuration for preparing input data sets and analyzing results, which leads users to error free processing with visual effects. Code validation and data analysis were performed by comparing the results of various calculations to the data outputs of previous programs such as MCNP 4B, ISOSHLD-II, QAD-CGGP, etc

Single-layer nano-carbon film, diamond film, and diamond/nano-carbon composite film field emission performance comparison

International Nuclear Information System (INIS)

Wang, Xiaoping; Wang, Jinye; Wang, Lijun

2016-01-01

A series of single-layer nano-carbon (SNC) films, diamond films, and diamond/nano-carbon (D/NC) composite films have been prepared on the highly doped silicon substrate by using microwave plasma chemical vapor deposition techniques. The films were characterised by scanning electron microscopy, Raman spectroscopy, and field emission I-V measurements. The experimental results indicated that the field emission maximum current density of D/NC composite films is 11.8–17.8 times that of diamond films. And the field emission current density of D/NC composite films is 2.9–5 times that of SNC films at an electric field of 3.0 V/μm. At the same time, the D/NC composite film exhibits the advantage of improved reproducibility and long term stability (both of the nano-carbon film within the D/NC composite cathode and the SNC cathode were prepared under the same experimental conditions). And for the D/NC composite sample, a high current density of 10 mA/cm"2 at an electric field of 3.0 V/μm was obtained. Diamond layer can effectively improve the field emission characteristics of nano-carbon film. The reason may be due to the diamond film acts as the electron acceleration layer.

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

Antimicrobial Activity of Single-Walled Carbon Nano tubes Suspended in Different Surfactants

International Nuclear Information System (INIS)

Dong, L.; Alex Henderson, A.; Field, Ch.

2012-01-01

We investigated the antibacterial activity of single-walled carbon nano tubes (SWCNTs) dispersed in surfactant solutions of sodium cholate, sodium dodecylbenzene sulfonate, and sodium dodecyl sulfate. Among the three surfactants, sodium cholate demonstrated the weakest antibacterial activity against Salmonella enterica, Escherichia coli, and Enterococcus faecium and thereby was used to disperse bundled SWCNTs in order to study nano tube antibiotic activity. SWCNTs exhibited antibacterial characteristics for both S. enterica and E. coli. With the increase of nano tube concentrations from 0.3 mg/mL to 1.5 mg/mL, the growth curves had plateaus at lower absorbance values whereas the absorbance value was not obviously affected by the incubation ranging from 5?min to 2 h. Our findings indicate that carbon nano tubes could become an effective alternative to antibiotics in dealing with drug-resistant and multidrug-resistant bacterial strains because of the physical mode of bactericidal action that SWCNTs display

Buried interfaces - A systematic study to characterize an adhesive interface at multiple scales

Science.gov (United States)

Haubrich, Jan; Löbbecke, Miriam; Watermeyer, Philipp; Wilde, Fabian; Requena, Guillermo; da Silva, Julio

2018-03-01

A comparative study of a model adhesive interface formed between laser-pretreated Ti15-3-3-3 and the thermoplastic polymer PEEK has been carried out in order to characterize the interfaces' structural details and the infiltration of the surface nano-oxide by the polymer at multiple scales. Destructive approaches such as scanning and transmission electron microscopy of microsections prepared by focused ion beam, and non-destructive imaging approaches including laser scanning and scanning electron microscopy of pretreated surfaces as well as synchrotron computed tomography techniques (micro- and ptychographic tomographies) were employed for resolving the large, μm-sized melt-structures and the fine nano-oxide substructure within the buried interface. Scanning electron microscopy showed that the fine, open-porous nano-oxide homogeneously covers the larger macrostructure features which in turn cover the joint surface. The open-porous nano-oxide forming the interface itself appears to be fully infiltrated and wetted by the polymer. No voids or even channels were detected down to the respective resolution limits of scanning and transmission electron microscopy.

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...

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.

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

Carrier mobility enhancement of nano-crystalline semiconductor films: Incorporation of redox -relay species into the grain boundary interface

Science.gov (United States)

Desilva, L. A.; Bandara, T. M. W. J.; Hettiarachchi, B. H.; Kumara, G. R. A.; Perera, A. G. U.; Rajapaksa, R. M. G.; Tennakone, K.

Dye-sensitized and perovskite solar cells and other nanostructured heterojunction electronic devices require securing intimate electronic contact between nanostructured surfaces. Generally, the strategy is solution phase coating of a hole -collector over a nano-crystalline high-band gap n-type oxide semiconductor film painted with a thin layer of the light harvesting material. The nano-crystallites of the hole - collector fills the pores of the painted oxide surface. Most ills of these devices are associated with imperfect contact and high resistance of the hole conducting layer constituted of nano-crystallites. Denaturing of the delicate light harvesting material forbid sintering at elevated temperatures to reduce the grain boundary resistance. It is found that the interfacial and grain boundary resistance can be significantly reduced via incorporation of redox species into the interfaces to form ultra-thin layers. Suitable redox moieties, preferably bonded to the surface, act as electron transfer relays greatly reducing the film resistance offerring a promising method of enhancing the effective hole mobility of nano-crystalline hole-collectors and developing hole conductor paints for application in nanostructured devices.

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.

Multi-level single mode 2D polymer waveguide optical interconnects using nano-imprint lithography

NARCIS (Netherlands)

Khan, M.U.; Justice, J.; Petäjä, J.; Korhonen, T.; Boersma, A.; Wiegersma, S.; Karppinen, M.; Corbett, B.

2015-01-01

Single and multi-layer passive optical interconnects using single mode polymer waveguides are demonstrated using UV nano-imprint lithography. The fabrication tolerances associated with imprint lithography are investigated and we show a way to experimentally quantify a small variation in index

Multiple kernel SVR based on the MRE for remote sensing water depth fusion detection

Science.gov (United States)

Wang, Jinjin; Ma, Yi; Zhang, Jingyu

2018-03-01

Remote sensing has an important means of water depth detection in coastal shallow waters and reefs. Support vector regression (SVR) is a machine learning method which is widely used in data regression. In this paper, SVR is used to remote sensing multispectral bathymetry. Aiming at the problem that the single-kernel SVR method has a large error in shallow water depth inversion, the mean relative error (MRE) of different water depth is retrieved as a decision fusion factor with single kernel SVR method, a multi kernel SVR fusion method based on the MRE is put forward. And taking the North Island of the Xisha Islands in China as an experimentation area, the comparison experiments with the single kernel SVR method and the traditional multi-bands bathymetric method are carried out. The results show that: 1) In range of 0 to 25 meters, the mean absolute error(MAE)of the multi kernel SVR fusion method is 1.5m,the MRE is 13.2%; 2) Compared to the 4 single kernel SVR method, the MRE of the fusion method reduced 1.2% (1.9%) 3.4% (1.8%), and compared to traditional multi-bands method, the MRE reduced 1.9%; 3) In 0-5m depth section, compared to the single kernel method and the multi-bands method, the MRE of fusion method reduced 13.5% to 44.4%, and the distribution of points is more concentrated relative to y=x.

Hydrogen storage in single-wall carbon nano-tubes by means of laser excitation

International Nuclear Information System (INIS)

Oksengorn, B.

2010-01-01

A new mode for hydrogen adsorption and storage in single-wall carbon nano-tubes is used, on the basis of laser excitation. Remember that this method has been useful to obtain, in the case of the fullerene C 60 , many complex C 60 -atoms or C 60 -molecules, where atoms or molecular particles are trapped inside the C 60 -molecules. We think this method might be important to store many hydrogen molecules inside carbon nano-tubes. (author)

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...

Single-photon sensitive fast ebCMOS camera system for multiple-target tracking of single fluorophores: application to nano-biophotonics

Science.gov (United States)

Cajgfinger, Thomas; Chabanat, Eric; Dominjon, Agnes; Doan, Quang T.; Guerin, Cyrille; Houles, Julien; Barbier, Remi

2011-03-01

Nano-biophotonics applications will benefit from new fluorescent microscopy methods based essentially on super-resolution techniques (beyond the diffraction limit) on large biological structures (membranes) with fast frame rate (1000 Hz). This trend tends to push the photon detectors to the single-photon counting regime and the camera acquisition system to real time dynamic multiple-target tracing. The LUSIPHER prototype presented in this paper aims to give a different approach than those of Electron Multiplied CCD (EMCCD) technology and try to answer to the stringent demands of the new nano-biophotonics imaging techniques. The electron bombarded CMOS (ebCMOS) device has the potential to respond to this challenge, thanks to the linear gain of the accelerating high voltage of the photo-cathode, to the possible ultra fast frame rate of CMOS sensors and to the single-photon sensitivity. We produced a camera system based on a 640 kPixels ebCMOS with its acquisition system. The proof of concept for single-photon based tracking for multiple single-emitters is the main result of this paper.

Direct electronic communication at bio-interfaces assisted by layered-metal-hydroxide slab arrays with controlled nano-micro structures.

Science.gov (United States)

An, Zhe; He, Jing

2011-10-28

The electronic transfer (eT) at bio-interfaces has been achieved by orientating 2D inorganic slabs in a regular arrangement with the slab ab-planes vertical to the electrode substrate. The eT rate is effectively promoted by tuning the nano-micro scale structures of perpendicular LDH arrays. This journal is © The Royal Society of Chemistry 2011

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.

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.

Combined Kernel-Based BDT-SMO Classification of Hyperspectral Fused Images

Directory of Open Access Journals (Sweden)

Fenghua Huang

2014-01-01

Full Text Available To solve the poor generalization and flexibility problems that single kernel SVM classifiers have while classifying combined spectral and spatial features, this paper proposed a solution to improve the classification accuracy and efficiency of hyperspectral fused images: (1 different radial basis kernel functions (RBFs are employed for spectral and textural features, and a new combined radial basis kernel function (CRBF is proposed by combining them in a weighted manner; (2 the binary decision tree-based multiclass SMO (BDT-SMO is used in the classification of hyperspectral fused images; (3 experiments are carried out, where the single radial basis function- (SRBF- based BDT-SMO classifier and the CRBF-based BDT-SMO classifier are used, respectively, to classify the land usages of hyperspectral fused images, and genetic algorithms (GA are used to optimize the kernel parameters of the classifiers. The results show that, compared with SRBF, CRBF-based BDT-SMO classifiers display greater classification accuracy and efficiency.

Surface, interface and thin film characterization of nano-materials using synchrotron radiation

International Nuclear Information System (INIS)

Kimura, Shigeru; Kobayashi, Keisuke

2005-01-01

From the results of studies in the nanotechnology support project of the Ministry of Education, Culture, Sports, Science and Technology of Japan, several investigations on the surface, interface and thin film characterization of nano-materials are described; (1) the MgB 2 thin film by X-ray diffraction, (2) the magnetism of the Pt thin film on a Co film by X-ray magnetic circular dichroism measurement, (3) the structure and physical properties of oxygen molecules absorbed in a micro hole of the cheleted polymer crystal by the direct observation in X-ray powder diffraction, and (4) the thin film gate insulator with a large dielectric constant, thermally treated HfO 2 /SiO 2 /Si, by X-ray photoelectron spectroscopy. (M.H.)

Thermal neutron scattering kernels for sapphire and silicon single crystals

International Nuclear Information System (INIS)

Cantargi, F.; Granada, J.R.; Mayer, R.E.

2015-01-01

Highlights: • Thermal cross section libraries for sapphire and silicon single crystals were generated. • Debye model was used to represent the vibrational frequency spectra to feed the NJOY code. • Sapphire total cross section was measured at Centro Atómico Bariloche. • Cross section libraries were validated with experimental data available. - Abstract: Sapphire and silicon are materials usually employed as filters in facilities with thermal neutron beams. Due to the lack of the corresponding thermal cross section libraries for those materials, necessary in calculations performed in order to optimize beams for specific applications, here we present the generation of new thermal neutron scattering kernels for those materials. The Debye model was used in both cases to represent the vibrational frequency spectra required to feed the NJOY nuclear data processing system in order to produce the corresponding libraries in ENDF and ACE format. These libraries were validated with available experimental data, some from the literature and others obtained at the pulsed neutron source at Centro Atómico Bariloche

A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

Science.gov (United States)

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

2017-06-19

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

Coupling DNA nano-breadboards to solid state conductors

International Nuclear Information System (INIS)

Wang, Liqian; Morales, Piero; Dalmastri, Claudia; Rapone, Bruno; Gothelf, Kurt; Krissanaprasit, Abhichart; Rettere, Scott

2015-01-01

DNA is not only a most extraordinary information storage medium: the programmable pairing of DNA single strands into precisely engineered, connecting double helices make it an extremely appealing material for assemblage of nanoscale architectures. This is the basis of DNA nanotechnology, and designing almost any structure made of DNA at the nanometer scale, decorating it with a variety of functional molecules, and accomplishing it by virtually inexpensive self-assembly, is already a reality in many research laboratories in the world. But can we extend the range of applications of this technology by coupling DNA grafted molecular electronic nano circuitry to solid state devices, and interface molecular smart functions to our senses? This challenging research is addressed by a collaborative research among ENEA, the Universities of Roma 'Tor Vergata' and 'Aarhus', and the CNMS of the Oak Ridge National Laboratory. The first results obtained by our consortium pave the way to the technological ability to interface and use completely self-assembled, DNA-based electronic nano-breadboards, endowed with ultra-high-density functional organic components [it

Electrical Crystallization Mechanism and Interface Characteristics of Nano wire Zn O/Al Structures Fabricated by the Solution Method

International Nuclear Information System (INIS)

Tseng, Y.W.; Hung, F.Y.; Lui, T.Sh.; Chen, Y.T.; Xiao, R.S.; Chen, K.J.

2012-01-01

Both solution nano wire Zn O and sputtered Al thin film on SiO 2 as the wire-film structure and the Al film were a conductive channel for electrical-induced crystallization (EIC). Direct current (DC) raised the temperature of the Al film and improved the crystallization of the nano structure. The effects of EIC not only induced Al atomic interface diffusion, but also doped Al on the roots of Zn O wires to form aluminum doped zinc oxide (AZO)/Zn O wires. The Al doping concentration and the distance of the Zn O wire increased with increasing the electrical duration. Also, the electrical current-induced temperature was ∼211 degree C (solid-state doped process) and so could be applied to low-temperature optoelectronic devices.

Managing collaboration in the nanoManipulator

DEFF Research Database (Denmark)

Hudson, Thomas C.; Helser, Aren T.; Sonnenwald, Diane H.

2004-01-01

We designed, developed, deployed, and evaluated the Collaborative nanoManipulator (CnM), a distributed, collaborative virtual environment system supporting remote scientific collaboration between users of the nanoManipulator interface to atomic force microscopes. This paper describes the entire...

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

DEFF Research Database (Denmark)

Li, Gang; Guan, Wei; Sierszecki, Krzysztof

2012-01-01

Rapid industrialisation has resulted in a demand for improved embedded control systems with features such as predictability, high processing performance and low power consumption. Software kernel implementation on a single processor is becoming more difficult to satisfy those constraints....... This paper presents a multi-core architecture incorporating a hardware kernel on FPGAs, intended for high performance applications in control engineering domain. First, the hardware kernel is investigated on the basis of a component-based real-time kernel HARTEX (Hard Real-Time Executive for Control Systems...

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.

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.

DNA damage due to perfluorooctane sulfonate based on nano-gold embedded in nano-porous poly-pyrrole film

Energy Technology Data Exchange (ETDEWEB)

Lu, Liping, E-mail: lipinglu@bjut.edu.cn; Xu, Laihui; Kang, Tianfang; Cheng, Shuiyuan

2013-11-01

DNA damage induced from perfluorooctane sulfonate (PFOS) was further developed on a nano-porous bionic interface. The interface was formed by assembling DNA on nano-gold particles which were embedded in a nano-porous overoxidized polypyrrole film (OPPy). Atomic force microscopy, scanning electron microscope and electrochemical investigations indicate that OPPy can be treated to form nano-pore structures. DNA damage due to PFOS was proved using electrochemistry and X-ray photoelectron spectroscopy (XPS) and was investigated by detecting differential pulse voltammetry (DPV) response of methylene blue (MB) which was used as electro-active indicator in the system. The current of MB attenuates obviously after incubation of DNA in PFOS. Moreover, electrochemical impedance spectroscopy (EIS) demonstrates that PFOS weakens DNA charge transport. The tentative binding ratio of PFOS: DNA base pair was obtained by analyzing XPS data of this system.

Effects of Two Purification Pretreatments on Electroless Copper Coating over Single-Walled Carbon Nano tubes

International Nuclear Information System (INIS)

Zheng, Z.; Li, L.; Dong, Sh.; Li, Sh.; Xiao, A.; Sun, Sh.

2014-01-01

To achieve the reinforcement of copper matrix composite by single-walled carbon nano tubes, a three-step-refluxing purification of carbon nano tubes sample with HNO 3 -NaOH-HCl was proposed and demonstrated. A previously reported purification process using an electromagnetic stirring with H 2 O 2 /HCl mixture was also repeated. Then, the purified carbon nano tubes were coated with copper by the same electroless plating process. At the end, the effects of the method on carbon nano tubes themselves and on copper coating were determined by transmission electron microscope spectroscopy, scanning electron microscope spectroscopy, X-ray diffractometry, thermogravimetric analysis, Fourier transformed infrared spectroscopy, and energy dispersive spectrometry. It was clearly confirmed that both of the two processes could remove most of iron catalyst particles and carbonaceous impurities without significant damage to carbon nano tubes. The thermal stability of the sample purified by H 2 O 2 /HCl treatment was slightly higher than that purified by HNO 3 -NaOH-HCl treatment. Nevertheless, the purification by HNO 3 -NaOH-HCl treatment was more effective for carboxyl functionalization on nano tubes than that by H 2 O 2 /HCl treatment. The Cu-coating on carbon nano tubes purified by both purification processes was complete, homogenous, and continuous. However, the Cu-coating on carbon nano tubes purified by H 2 O 2 /HCl was oxidized more seriously than those on carbon nano tubes purified by HNO 3 -NaOH-HCl treatment.

Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

KAUST Repository

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

2017-01-01

Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

Batched Triangular Dense Linear Algebra Kernels for Very Small Matrix Sizes on GPUs

KAUST Repository

Charara, Ali

2017-03-06

Batched dense linear algebra kernels are becoming ubiquitous in scientific applications, ranging from tensor contractions in deep learning to data compression in hierarchical low-rank matrix approximation. Within a single API call, these kernels are capable of simultaneously launching up to thousands of similar matrix computations, removing the expensive overhead of multiple API calls while increasing the occupancy of the underlying hardware. A challenge is that for the existing hardware landscape (x86, GPUs, etc.), only a subset of the required batched operations is implemented by the vendors, with limited support for very small problem sizes. We describe the design and performance of a new class of batched triangular dense linear algebra kernels on very small data sizes using single and multiple GPUs. By deploying two-sided recursive formulations, stressing the register usage, maintaining data locality, reducing threads synchronization and fusing successive kernel calls, the new batched kernels outperform existing state-of-the-art implementations.

Carbon nanotube growth from catalytic nano-clusters formed by hot-ion-implantation into the SiO{sub 2}/Si interface

Energy Technology Data Exchange (ETDEWEB)

Hoshino, Yasushi, E-mail: yhoshino@kanagawa-u.ac.jp [Department of Information Sciences, Kanagawa University, 2946 Tsuchiya, Hiratsuka, Kanagawa 259-1293 (Japan); Arima, Hiroki; Yokoyama, Ai; Saito, Yasunao; Nakata, Jyoji [Department of Information Sciences, Kanagawa University, 2946 Tsuchiya, Hiratsuka, Kanagawa 259-1293 (Japan)

2012-07-01

We have studied growth of chirality-controlled carbon nanotubes (CNTs) from hot-implantation-formed catalytic nano-clusters in a thermally grown SiO{sub 2}/Si substrate. This procedure has the advantage of high controllability of the diameter and the number of clusters by optimizing the conditions of the ion implantation. In the present study, Co{sup +} ions with ion dose of 8 Multiplication-Sign 10{sup 16} cm{sup -2} are implanted in the vicinity of the SiO{sub 2}/Si interface at 300 Degree-Sign C temperature. The implanted Co atoms located in the SiO{sub 2} layer has an amorphous-like structure with a cluster diameter of several nm. In contrast, implanted Co atoms in the Si substrate are found to take a cobalt silicide structure, confirmed by the high-resolution image of transmission electron microscope. CNTs are grown by microwave-plasma-enhanced chemical vapor deposition. We have confirmed a large amount of vertically-aligned multi-walled CNTs from the Co nano-clusters formed by the hot-ion-implantation near the SiO{sub 2}/Si interface.

Oriented nano-wire formation and selective adhesion on substrates by single ion track reaction in polysilanes

International Nuclear Information System (INIS)

Shu Seki; Satoshi Tsukuda, Yoichi Yoshida; Seiichi Tagawa; Masaki Sugimoto; Shigeru Tanaka

2002-01-01

1-D nano-sized materials such as carbon nanotubes have attracted much attention as ideal quantum wires for future manufacturing techniques of nano-scaled opto-electronic devices. However it is still difficult to control the sizes, spatial distributions, or positions of nanotubes by conventional synthetic techniques to date. The MeV order heavy ion beams causes ultra-high density energy deposition which can not be realized by any other techniques (lasers, H, etc), and penetrate the polymer target straighforward as long as 1∼100 m depth. the energy deposited area produces non-homogeneous field can be controlled by changing the energy deposition rate of incident ions (LET: linear energy transfer, eV/nm). We found that cross-linking reaction of polysilane derivatives was predominantly caused and gave nano-gel in the chemical core, unlike main chain scission occurring at the outside of the area. high density energy deposition by ion beams causes non-homogeneous crosslinking reaction of polysilane derivatives within a nano-sized cylindrical area along an ion trajectory, and gives -SiC based nano-wires of which sizes (length, thickness) and number densities are completely under control by changing the parameters of incident ion beams and molecular sizes of target polymers. based on the concept pf the single track gelation, the present study demonstrates the formation of cross-linked polysilane nano-wires with the fairly controlled sizes. Recently the techniques of position-selective single ion hitting have been developed for MeV order ion beams, however it is not sufficient to control precisely the positions of the nano-wires on the substrates within sub- m area. in the present study, we report the selective adhesion of anno-wires on Si substrates by the surface treatments before coating, which enables the patterning of planted nano-wires on substrates and/or electrodes as candidates for nano-sized field emissive cathodes or electro-luminescent devices. Some examples of

Controllable preparation of copper phthalocyanine single crystal nano column and its chlorine gas sensing properties

Directory of Open Access Journals (Sweden)

Jianhong Zhao

2016-09-01

Full Text Available The unsubstituted copper phthalocyanine (CuPc single crystal nano columns were fabricated for the first time as chlorine (Cl2 gas sensors in this paper. The nano columns of CuPc have been prepared on different substrates via template-free physical vapor deposition (PVD approach. The growth mechanism of CuPc nano column on quartz was explored and the same condition used on other substrates including glass, sapphire (C-plane, M-plane, R-plane, Si and SiO2/Si came to a same conclusion, which confirmed that the aligned growth of CuPc nano column is not substrate-dependent. And then the CuPc nano column with special morphology was integrated as in-situ sensor device which exhibits high sensitivity and selectivity towards Cl2 at room temperature with a minimum detection limit as low as 0.08 ppm. The response of sensor was found to increase linearly (26∼659% with the increase for Cl2 within concentration range (0.08∼4.0ppm. These results clearly demonstrate the great potential of the nano column growth and device integration approach for sensor device.

Jdpd: an open java simulation kernel for molecular fragment dissipative particle dynamics.

Science.gov (United States)

van den Broek, Karina; Kuhn, Hubert; Zielesny, Achim

2018-05-21

Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The new kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated "all-in-one" simulation systems.

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.

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

Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

Science.gov (United States)

Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

2014-01-01

This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

Multi-dimensional single-spin nano-optomechanics with a levitated nanodiamond

Science.gov (United States)

Neukirch, Levi P.; von Haartman, Eva; Rosenholm, Jessica M.; Nick Vamivakas, A.

2015-10-01

Considerable advances made in the development of nanomechanical and nano-optomechanical devices have enabled the observation of quantum effects, improved sensitivity to minute forces, and provided avenues to probe fundamental physics at the nanoscale. Concurrently, solid-state quantum emitters with optically accessible spin degrees of freedom have been pursued in applications ranging from quantum information science to nanoscale sensing. Here, we demonstrate a hybrid nano-optomechanical system composed of a nanodiamond (containing a single nitrogen-vacancy centre) that is levitated in an optical dipole trap. The mechanical state of the diamond is controlled by modulation of the optical trapping potential. We demonstrate the ability to imprint the multi-dimensional mechanical motion of the cavity-free mechanical oscillator into the nitrogen-vacancy centre fluorescence and manipulate the mechanical system's intrinsic spin. This result represents the first step towards a hybrid quantum system based on levitating nanoparticles that simultaneously engages optical, phononic and spin degrees of freedom.

The fabrication and single electron transport of Au nano-particles placed between Nb nanogap electrodes

International Nuclear Information System (INIS)

Nishino, T; Negishi, R; Ishibashi, K; Kawao, M; Nagata, T; Ozawa, H

2010-01-01

We have fabricated Nb nanogap electrodes using a combination of molecular lithography and electron beam lithography. Au nano-particles with anchor molecules were placed in the gap, the width of which could be controlled on a molecular scale (∼2 nm). Three different anchor molecules which connect the Au nano-particles and the electrodes were tested to investigate their contact resistance, and a local gate was fabricated underneath the Au nano-particles. The electrical transport measurements at liquid helium temperatures indicated single electron transistor (SET) characteristics with a charging energy of about ∼ 5 meV, and a clear indication of the effect of superconducting electrodes was not observed, possibly due to the large tunnel resistance.

Nano materials for Energy and Environmental Applications

International Nuclear Information System (INIS)

Srinivasan, S.; Kannan, A.M.; Kothurkar, N.; Khalil, Y.; Kuravi, S.

2015-01-01

Nano materials enabled technologies have been seamlessly integrated into applications such as aviation and space, chemical industry, optics, solar hydrogen, fuel cell, batteries, sensors, power generation, aeronautic industry, building/construction industry, automotive engineering, consumer electronics, thermoelectric devices, pharmaceuticals, and cosmetic industry. Clean energy and environmental applications often demand the development of novel nano materials that can provide shortest reaction pathways for the enhancement of reaction kinetics. Understanding the physicochemical, structural, microstructural, surface, and interface properties of nano materials is vital for achieving the required efficiency, cycle life, and sustain ability in various technological applications. Nano materials with specific size and shape such as nano tubes, nano fibers/nano wires, nano cones, nano composites, nano rods, nano islands, nanoparticles, nanospheres, and nano shells to provide unique properties can be synthesized by tuning the process conditions.

Simultaneous positioning and orientation of a single nano-object by flow control: theory and simulations

International Nuclear Information System (INIS)

Mathai, Pramod P; Berglund, Andrew J; Alexander Liddle, J; Shapiro, Benjamin A

2011-01-01

In this paper, we theoretically describe a method to simultaneously control both the position and orientation of single nano-objects in fluids by precisely controlling the flow around them. We develop and simulate a control law that uses electro-osmotic flow (EOF) actuation to translate and rotate rigid nano-objects in two spatial dimensions. Using EOF to control nano-objects offers advantages as compared to other approaches: a wide class of objects can be manipulated (no magnetic or electric dipole moments are needed), the object can be controlled over a long range (>100 μm) with sub-micrometer accuracy, and control may be achieved with simple polydimethylsiloxane (PDMS) devices. We demonstrate the theory and numerical solutions that will enable deterministic control of the position and orientation of a nano-object in solution, which can be used, for example, to integrate nanostructures in circuits and orient sensors to probe living cells.

Nano-scale observations of interface between lichen and basaltic rock: Pseudomorphic growth of amorphous silica on augite

Science.gov (United States)

Tamura, T.; Kyono, A.; Kebukawa, Y.; Takagi, S.

2017-12-01

Recently, lichens as the earliest colonizers of terrestrial habitats are recognized to accelerate the mineral degradation at the interface between lichens and surface rocks. Much interest has been therefore devoted in recent years to the weathering induced by the lichen colonization. Here, we report nano-scale observations of the interface between lichens and basaltic rock by TEM and STXM techniques. Some samples of basaltic rocks totally covered by lichens were collected from the 1986 lava flows on the northwest part of Izu-Oshima volcano, Japan. To prepare specimens for the nano-scale observation, we utilized the focused ion beam (FIB) system. The microstructure and local chemistry of the specimens were thoroughly investigated by TEM equipped with energy-dispersive X-ray spectroscopy (EDX). Chemical components and chemical heterogeneity at the interface were observed by scanning transmission X-ray microscopy (STXM) at Advanced Light Source branch line 5.3.2.2. The collected rocks were classified into the augite-pigeonite-bronzite basalt including 6 to 8% plagioclase phenocrysts. The lichens adhering to the rocks were mainly Stereocaulon vesuvianum, fruticose lichen, which are widespread over the study area. The metabolites of the Stereocaulon vesuvianum exhibited a mean pH of 4.5 and dominance by acids. The STEM-EDX observations revealed that the interface between augite and the lichen was completely covered with amorphous silica multilayer with a thickness of less than 1 µm. Ca L-edge XANES spectra of the augite showed that the energy profile of the absorption edge at 349 eV was varied with the depth from the surface, indicating that the M2 site coordination accommodating Ca2+ undergoes significant change in shape as a function of distance from the surface. This behavior results from the fact that the M2 site is more distorted and more flexible in the C2/c clinopyroxene phase. Taking into consideration that the S. vesuvianum can produce acidic organic compounds

A Realization of Temperature Monitoring System Based on Real-Time Kernel μC/OS and 1-wire Bus

Directory of Open Access Journals (Sweden)

Yanmei Qi

2013-06-01

Full Text Available The traditional temperature monitoring system generally adopt some analog sensors for collecting data and a microcontroller for processing data for the purpose of temperature monitoring. However, this back-fore ground system has the disadvantages that the system has poor real-time property and single function, the amount of sensors is not easy to expand, and the software system has a difficulty in upgrading. Aiming at these disadvantages, the system designed in this paper adopts brand-new hardware and software structures: a digitaltemperature sensor array is connected to 1-wire bus and communicated with a control core through 1-wire bus protocol, thus a great convenience is provided for the expansion of the sensor; a real-time operating system is introduced into the software, an application program capable of realizing various functions runs on the real-time kernel μC/OS-II platform. The application of the real-time kernel also provides a good lower layer interface for the late-stage software upgrading.

Direct writing of large-area micro/nano-structural arrays on single crystalline germanium substrates using femtosecond lasers

Science.gov (United States)

Li, Lin; Wang, Jun

2017-06-01

A direct writing technique for fabricating micro/nano-structural arrays without using a multi-scanning process, multi-beam interference, or any assisted microlens arrays is reported. Various sub-wavelength micro/nano-structural arrays have been directly written on single crystalline germanium substrate surfaces using femtosecond laser pulses. The evolution of the multiscale surface morphology from periodic micro/nano-structures to V-shaped microgrooves has been achieved, and the relationship between array characteristics and laser polarization directions has been discussed. The self-organization model agrees well with the experimental results in this study.

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.

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.

Self-aligned periodic Ni nano dots embedded in nano-oxide layer

International Nuclear Information System (INIS)

Doi, M.; Izumi, M.; Kawasaki, S.; Miyake, K.; Sahashi, M.

2007-01-01

The Ni nano constriction dots embedded in the Ta-nano-oxide layer (NOL) was prepared by the ion beam sputtering (IBS) method. After the various conditions of the oxidations, the structural analyses of the NOL were performed by RHEED, AES and in situ STM/AFM observations. From the current image of the conductive AFM for NOL, the periodically aligned metallic dots with the size around 5-10 nm were successfully observed. The mechanism of the formation of the self-organized aligned Ni nano constriction dots is discussed from the standpoint of the grain size, the crystal orientation, the preferred oxidation of Ta at the diffused interface

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

KAUST Repository

Rosen, Paul

2013-01-01

We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

KAUST Repository

Rosen, Paul

2013-06-01

We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.

The gold standard: gold nanoparticle libraries to understand the nano-bio interface.

Science.gov (United States)

Alkilany, Alaaldin M; Lohse, Samuel E; Murphy, Catherine J

2013-03-19

Since the late 1980s, researchers have prepared inorganic nanoparticles of many types--including elemental metals, metal oxides, metal sulfides, metal selenides, and metal tellurides--with excellent control over size and shape. Originally many researchers were primarily interested in exploring the quantum size effects predicted for such materials. Applications of inorganic nanomaterials initially centered on physics, optics, and engineering but have expanded to include biology. Many current nanomaterials can serve as biochemical sensors, contrast agents in cellular or tissue imaging, drug delivery vehicles, or even as therapeutics. In this Account we emphasize that the understanding of how nanomaterials will function in a biological system relies on the knowledge of the interface between biological systems and nanomaterials, the nano-bio interface. Gold nanoparticles can serve as excellent standards to understand more general features of the nano-bio interface because of its many advantages over other inorganic materials. The bulk material is chemically inert, and well-established synthetic methods allow researchers to control its size, shape, and surface chemistry. Gold's background concentration in biological systems is low, which makes it relatively easy to measure it at the part-per-billion level or lower in water. In addition, the large electron density of gold enables relatively simple electron microscopic experiments to localize it within thin sections of cells or tissue. Finally, gold's brilliant optical properties at the nanoscale are tunable with size, shape, and aggregation state and enable many of the promising chemical sensing, imaging, and therapeutic applications. Basic experiments with gold nanoparticles and cells include measuring the toxicity of the particles to cells in in vitro experiments. The species other than gold in the nanoparticle solution can be responsible for the apparent toxicity at a particular dose. Once the identity of the toxic

Option Valuation with Volatility Components, Fat Tails, and Non-Monotonic Pricing Kernels

DEFF Research Database (Denmark)

Babaoglu, Kadir; Christoffersen, Peter; Heston, Steven L.

We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A U-shaped pricing kernel is economically most im...

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.

Experiences implementing the MPI standard on Sandia`s lightweight kernels

Energy Technology Data Exchange (ETDEWEB)

Brightwell, R.; Greenberg, D.S.

1997-10-01

This technical report describes some lessons learned from implementing the Message Passing Interface (MPI) standard, and some proposed extentions to MPI, at Sandia. The implementations were developed using Sandia-developed lightweight kernels running on the Intel Paragon and Intel TeraFLOPS platforms. The motivations for this research are discussed, and a detailed analysis of several implementation issues is presented.

Synthesis of NaCl Single Crystals with Defined Morphologies as Templates for Fabricating Hollow Nano/micro-structures

DEFF Research Database (Denmark)

Wang, B.B.; Jin, P.; Yue, Yuanzheng

2015-01-01

. These naturally abundant NaCl single crystal templates are water-soluble, environmentally-friendly and uniform in both geometry and size, and hence are ideal for preparing high quality hollow nano/micro structures. The new approach may have the potential to replace the conventional hard or soft template...... approaches. Furthermore, this work has revealed the formation mechanism of nano/micron NaCl crystals with different sizes and geometries....

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.

Carbon nano tubes embedded in polymer nano fibers

International Nuclear Information System (INIS)

Dror, Y.; Kedem, S.; Khalfin, R.L.; Paz, Y.; Cohenl, Y.; Salalha, Y.; Yarin, A.L.; Zussman, A.

2004-01-01

Full Text: The electro spinning process was used successfully to embed Multi-walled carbon nano tubes (MWCNTs) and single-walled carbon nano tubes (SWCNTs) in a matrix of poly(ethylene oxide) (PEO) forming composite nano fibers. Initial dispersion of SWCNTs in water was achieved by the use of an amphphilic alternating copolymer of styrene and sodium maleate. MWNT dispersion was achieved by ionic and nonionic surfactants. The distribution and conformation of the nano tubes in the nano fibers were studied by transmission electron microscopy (TEM). Oxygen plasma etching was used to expose the nano tubes within the nano fibers to facilitate direct observation. Nano tube alignment within the nano fibers was shown to depend strongly on the quality of the initial dispersions. Well-dispersed and separated nano tubes were embedded in a straight and aligned form while entangled non-separated nano tubes were incorporated as dense aggregates. X-ray diffraction demonstrated a high degree of orientation of the PEO crystals in the electro spun nano fibers with embedded SWCNTs, whereas incorporation of MVCNTs had a detrimental effect on the polymer orientation. Composite polymer nano fibers containing dispersed phases of nanometric TiO 2 particles and MWCNTs were also prepared electro spinning. In this case, the polymer matrix was poly(acrylonitrile) (PAN). The morphology and possible applications of these composite nano fibers will be discussed

A Histological Study of Aspergillus flavus Colonization of Wound Inoculated Maize Kernels of Resistant and Susceptible Maize Hybrids in the Field

Directory of Open Access Journals (Sweden)

Gary L. Windham

2018-04-01

Full Text Available Aspergillus flavus colonization in developing kernels of maize single-cross hybrids resistant (Mp313E × Mp717 and susceptible (GA209 × T173 to aflatoxin accumulation was determined in the field over three growing seasons (2012–2014. Plants were hand pollinated, and individual kernels were inoculated with a needle dipped in a suspension of A. flavus conidia 21 days after pollination. Kernels were harvested at 1- to 2-day intervals from 1 to 21 days after inoculation (DAI. Kernels were placed in FAA fixative, dehydrated, embedded in paraffin, sectioned, and stained with toluidine blue. Kernels were also collected additional kernels for aflatoxin analyses in 2013 and 2014. At 2 DAI, A. flavus hyphae were observed among endosperm cells in the susceptible hybrid, but colonization of the endosperm in the resistant hybrid was limited to the wound site of the resistant hybrid. Sections of the scutellum of the susceptible hybrid were colonized by A. flavus by 5 DAI. Fungal growth was slower in the resistant hybrid compared to the susceptible hybrid. By 10 DAI, A. flavus had colonized a large section of the embryo in the susceptible hybrid; whereas in the resistant hybrid, approximately half of the endosperm had been colonized and very few cells in the embryo were colonized. Fungal colonization in some of the kernels of the resistant hybrid was slowed in the aleurone layer or at the endosperm-scutellum interface. In wounded kernels with intact aleurone layers, the fungus spread around the kernel between the pericarp and aleurone layer with minimal colonization of the endosperm. Aflatoxin B1 was first detected in susceptible kernel tissues 8 DAI in 2013 (14 μg/kg and 2014 (18 μg/kg. The resistant hybrid had significantly lower levels of aflatoxin accumulation compared to the susceptible hybrid at harvests 10, 21, and 28 DAI in 2013, and 20 and 24 DAI in 2014. Our study found differential A. flavus colonization of susceptible and resistant kernel

Chip-package nano-structured copper and nickel interconnections with metallic and polymeric bonding interfaces

Science.gov (United States)

Aggarwal, Ankur

developed to address the IC packaging requirements beyond the ITRS projections and to introduce innovative design and fabrication concepts that will further advance the performance of the chip, the package, and the system board. The nano-structured interconnect technology simultaneously packages all the ICs intact in wafer form with quantum jump in the number of interconnections with the lowest electrical parasitics. The intrinsic properties of nano materials also enable several orders of magnitude higher interconnect densities with the best mechanical properties for the highest reliability and yet provide higher current and heat transfer densities. Nano-structured interconnects provides the ability to assemble the packaged parts on the system board without the use of underfill materials and to enable advanced analog/digital testing, reliability testing, and burn-in at wafer level. This thesis investigates the electrical and mechanical performance of nanostructured interconnections through modeling and test vehicle fabrication. The analytical models evaluate the performance improvements over solder and compliant interconnections. Test vehicles with nano-interconnections were fabricated using low cost electro-deposition techniques and assembled with various bonding interfaces. Interconnections were fabricated at 200 micron pitch to compare with the existing solder joints and at 50 micron pitch to demonstrate fabrication processes at fine pitches. Experimental and modeling results show that the proposed nano-interconnections could enhance the reliability and potentially meet all the system performance requirements for the emerging micro/nano-systems.

A Fabrication Technique for Nano-gap Electrodes by Atomic Force Microscopy Nano lithography

International Nuclear Information System (INIS)

Jalal Rouhi; Shahrom Mahmud; Hutagalung, S.D.; Kakooei, S.

2011-01-01

A simple technique is introduced for fabrication of nano-gap electrodes by using nano-oxidation atomic force microscopy (AFM) lithography with a Cr/ Pt coated silicon tip. AFM local anodic oxidation was performed on silicon-on-insulator (SOI) surfaces by optimization of desired conditions to control process in contact mode. Silicon electrodes with gaps of sub 31 nm were fabricated by nano-oxidation method. This technique which is simple, controllable, inexpensive and fast is capable of fabricating nano-gap structures. The current-voltage measurements (I-V) of the electrodes demonstrated very good insulating characteristics. The results show that silicon electrodes have a great potential for fabrication of single molecule transistors (SMT), single electron transistors (SET) and the other nano electronic devices. (author)

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

Directory of Open Access Journals (Sweden)

Chenchao Zhao

2018-01-01

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

Interfaces anisotropy in single crystal V/Fe/V trilayer

Energy Technology Data Exchange (ETDEWEB)

Louis, D. [Institut Jean Lamour, UMR CNRS 7198, Université de Lorraine, 54506 Vandoeuvre-lès-Nancy (France); Lytvynenko, Ia. [Sumy State University, 2, Rymskogo-Korsakova Street, 40007 Sumy (Ukraine); Hauet, T., E-mail: thomas.hauet@univ-lorraine.fr [Institut Jean Lamour, UMR CNRS 7198, Université de Lorraine, 54506 Vandoeuvre-lès-Nancy (France); Lacour, D.; Hehn, M.; Andrieu, S.; Montaigne, F. [Institut Jean Lamour, UMR CNRS 7198, Université de Lorraine, 54506 Vandoeuvre-lès-Nancy (France)

2014-12-15

The value and sign of V/Fe interface anisotropy are investigated. Epitaxial V/Fe/V/Au layers with different iron thicknesses were grown on single-crystalline (001) MgO substrate by ultra-high vacuum molecular beam epitaxy. Magnetometry was used to measure magnetization and out-of-plane anisotropy field. From these values, we quantify the number of dead layers due to V/Fe or Fe/V interfaces, and compare it with the literature. We deduce that dead layers occur mostly at the bottom V/Fe interface. An average value for V/Fe and Fe/V interface anisotropy around 0±0.1 erg/cm{sup 2} (mJ/m{sup 2}) was thus deduced. - Highlights: • In a V/Fe/V stack, dead layers (i.e. overall magnetization reduction) originate mostly from the bottom V/Fe interface. • The average value for V/Fe and Fe/V interface anisotropy in V/Fe/V stack has been quantified as 0±0.1 erg/cm{sup 2} (mJ/m{sup 2})

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.

A Study of Umbilical Communication Interface of Simulator Kernel to Enhance Visibility and Controllability

Science.gov (United States)

Koo, Cheol Hea; Lee, Hoon Hee; Moon, Sung Tae; Han, Sang Hyuck; Ju, Gwang Hyeok

2013-08-01

In aerospace research and practical development area, increasing the usage of simulation in software development, component design and system operation has been maintained and the increasing speed getting faster. This phenomenon can be found from the easiness of handling of simulation and the powerfulness of the output from the simulation. Simulation brings lots of benefit from the several characteristics of it as following, - easy to handle ; it is never broken or damaged by mistake - never wear out ; it is never getting old - cost effective ; once it is built, it can be distributed over 100 ~ 1000 people GenSim (Generic Simulator) which is developing by KARI and compatible with ESA SMP standard provides such a simulation platform to support flight software validation and mission operation verification. User interface of GenSim is shown in Figure 1 [1,2]. As shown in Figure 1, as most simulation platform typically has, GenSim has GRD (Graphical Display) and AND (Alpha Numeric Display). But frequently more complex and powerful handling of the simulated data is required at the actual system validation for example mission operation. In Figure 2, system simulation result of COMS (Communication, Ocean, and Meteorological Satellite, launched at June 28 2008) is being drawn by Celestia 3D program. In this case, the needed data from Celestia is given by one of the simulation model resident in system simulator through UDP network connection in this case. But the requirement of displaying format, data size, and communication rate is variable so developer has to manage the connection protocol manually at each time and each case. It brings a chaos in the simulation model design and development, also to the performance issue at last. Performance issue is happen when the required data magnitude is higher than the capacity of simulation kernel to process the required data safely. The problem is that the sending data to a visualization tool such as celestia is given by a

AC dielectrophoresis alignment of single-walled carbon nano tubes (SWNTS) and palladium nano wires for hydrogen gas sensor

International Nuclear Information System (INIS)

Nur Ubaidah Saidin; Nur Ubaidah Saidin; Ying, K.K.; KKhuan, N.I.; Mohammad Hafizuddin Jumali

2013-01-01

Full-text: Using AC electric field, nano wires or nano tubes can be aligned, chained or accelerated in a direction parallel to the applied field, oriented or concentrated onto designated locations as well as dispersed in controlled manner under high efficiencies. In this work, systematic study on the alignment of nano wires/ nano tubes across the 3 μm-gaps between pairs of micro fabricated gold electrodes was carried out using AC dielectrophoresis technique. Densities and alignment of the nano wires/ nano tubes across the gaps of the electrodes were controlled by the applied AC field strengths and frequencies on the electrodes. Good alignments of SWNTs and Pd nano wires were achieved at an applied frequency of 5 MHz and a field strength as high as 25 V pp for Pd nano wires compared to only 2 V pp for SWNTs. The aligned nano wires/ nano tubes will be functioned as sensor elements for hydrogen gas sensing. (author)

Ab initio molecular dynamics study of thermite reaction at Al and CuO nano-interfaces at different temperatures

Science.gov (United States)

Tang, Cui-Ming; Chen, Xiao-Xu; Cheng, Xin-Lu; Zhang, Chao-Yang; Lu, Zhi-Peng

2018-05-01

The thermite reaction at Al/CuO nano-interfaces is investigated with ab initio molecular dynamics calculations in canonical ensemble at 500 K, 800 K, 1200 K and 1500 K, respectively. The reaction process and reaction products are analyzed in terms of chemical bonds, average charge, time constants and total potential energy. The activity of the reactants enhances with increasing temperature, which induces a faster thermite reaction. The alloy reaction obviously expands outward at Cu-rich interface of Al/CuO system, and the reaction between Al and O atoms obviously expands outward at O-rich interface as temperature increases. Different reaction products are found at the outermost layer of different interfaces in the Al/CuO system. In generally, the average charge of the outer layer aluminum atoms (i.e., Al1, Al2, Al5 and Al6) increases with temperature. The potential energy of Al/CuO system decreases significantly, which indicates that drastic exothermic reaction occurs at the Al/CuO system. This research enhances fundamental understanding in temperature effect on the thermite reaction at atomic level, which can potentially open new possibilities for its industrial application.

Application of the functional surface/interface of Nano/Micro systems

Science.gov (United States)

Zeng, Xiping

Investigation of the surface/ interface of Nano/Micro systems plays an essential role in lots of areas, include the synthesis and assembly of nanostructures, evaporation of liquid, etc. Through studying the interaction between the polyvinyl pyrrolidone (PVP) and the surface of the silver nanowires (AgNWs), it was found that the PVP, serving as a capping agent, has a great impact on the morphology and structure of AgNWs. By means of a series of experiments, the critical minimum PVP chain length for successful formation of uniform nanowires was discovered, below which, only nanoparticles or short Nano rods can be obtained. Surprisingly, a core-shell structure of nanowire with a polycrystal was observed when the PVP with very long chain length was employed in the processing. By controlling the interaction between the Ag NWs and the surface of the substrates, a one-step method was developed for the fabrication of electrodes with patterns. Such film comprising Ag NWs were only self-growing or grafted on a hydrophilic surface area instead of the hydrophobic one. Thus, the selective patterning of the conducting film on the hybrid substrate surface can be realized, which is etching-free method for metal removal usually for the fabrication of electrodes by lithographic process or laser cutting. Therefore, such technique for producing conducting film is green and environmental friendly. A biochip based silver nano dendritic structures was fabricated to detect Carcinoembryonic antigen (CEA), which is a common tumor marker in clinical tests. Results show that the Raman signal of the CEA enhanced by about 10 4 times compared with silver nanowires, which is capable of detecting CEA at 1 fg/mL. The surface of liquid water, especial the hydration of ions on the surface, which are of fundamental interest and have potential applications, remain unclear. A fantastic and extraordinary phenomenon was observed during the evaporation of a water droplet doped with manganese chloride. As

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...

Study of the Emission Characteristics of Single-Walled CNT and Carbon Nano-Fiber Pyrograf III

Science.gov (United States)

Mousa, Marwan S.; Al-Akhras, M.-Ali H.; Daradkeh, Samer

2018-02-01

Field emission microscopy measurements from Single-Walled Carbon Nanotubes (SWCNTs) and Carbon Nano-Fibers Pyrograf III PR-1 (CNF) were performed. Details of the materials employed in the experiments are as follows: (a) Carbon Nano-Fibers Pyrograf III PR-1 (CNF), having an average fiber diameter that is ranging between (100-200) nm with a length of (30-100) μm. (b) Single walled Carbon Nanotubes were produced by high-pressure CO over Fe particle (HiPCO: High-Pressure Carbon Monoxide process), having an average diameter ranging between (1-4) nm with a length of (1-3) μm. The experiments were performed under vacuum pressure value of (10-7 mbar). The research work reported here includes the field electron emission current-voltage (I-V) characteristics and presented as Fowler-Nordheim (FN) plots and the spatial emission current distributions (electron emission images) obtained and analyzed in terms of electron source features. For both the SWCNT and the CNF a single spot pattern for the electron spatial; distributions were observed.

Light hydrogen isotopes in the single - walled carbon nano tube

International Nuclear Information System (INIS)

Khugaev, A.V.; Sultanov, R.A.; Guster, D.

2007-01-01

Full text: Progress of our understanding of the molecular hydrogen behavior in the nano tube interior open an intriguing possibility for the applications of these knowledge's to the solution of the hydrogen storage problem and light isotopes gas selectivity. That can strongly change the situation at the energy production in the world and completely change our civil life. These investigations underline the influence of the quantum effects on the properties of molecular hydrogen in the nano tube interior and it leads to the pure quantum-mechanical reformulation of the problem for the hydrogen behavior inside carbon nano tube as a problem of molecular quantum system behavior in the external field induced by the regular nano tube surface. In the present paper the molecular hydrogen behavior in the carbon nano tube was considered in the simple quantum mechanical manner. The main attention was paid to the investigation of the quantum sieving selectivity in the dependence of nano tube composition, radius and symmetry properties. For the interaction potential between hydrogen and nano tube surface was taken some phenomenological LJ(12,6) - (Lennard - Jones) potential and the external field induced by the nano tube in its interior is considered as a simple sum over the all nano tube carbon atoms. Influence of the structure of rotation (vibration) spectrum of the energy levels of diatomic molecules, such as H 2 , HD and D 2 on the final results and finite size of the nano tube along the axis of symmetry, its boundary effects is discussed in details. Thermal oscillations of nano tube surface were considered separately in the dependence of the temperature gradient along of the axis of symmetry

Single-kernel analysis of fumonisins and other fungal metabolites in maize from South African subsistence farmers

DEFF Research Database (Denmark)

Mogensen, Jesper Mølgaard; Sørensen, S.M.; Sulyok, M.

2011-01-01

Fumonisins are important Fusarium mycotoxins mainly found in maize and derived products. This study analysed maize from five subsistence farmers in the former Transkei region of South Africa. Farmers had sorted kernels into good and mouldy quality. A total of 400 kernels from 10 batches were...... analysed; of these 100 were visually characterised as uninfected and 300 as infected. Of the 400 kernels, 15% were contaminated with 1.84-1428 mg kg(-1) fumonisins, and 4% (n = 15) had a fumonisin content above 100 mg kg(-1). None of the visually uninfected maize had detectable amounts of fumonisins....... The total fumonisin concentration was 0.28-1.1 mg kg(-1) for good-quality batches and 0.03-6.2 mg kg(-1) for mouldy-quality batches. The high fumonisin content in the batches was apparently caused by a small number (4%) of highly contaminated kernels, and removal of these reduced the average fumonisin...

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

Solid-melt interface structure and growth of Cu alloy single crystals

International Nuclear Information System (INIS)

Tomimitsu, Hiroshi; Kamada, Kohji.

1983-01-01

Crystal-melt interface behavior during the growth of Cu-base solid solutions by the Bridgman method is discussed on the basis of experimental evidence obtained by neutron diffraction topography. Advantages of neutron diffraction topography for the characterization of large single crystals, such as dealt with in this paper, are emphasized. Evidence was odserved of extremely regular crystal growth along directions, irrespective of the macroscopic growth direction. This contrasts with the previously believed (110) normal growth which is a conclusion of growth theory based on molecular kinetics at the solid-melt interface. In consequence, we believe that the kinetics at the interface is a minor factor in the meltgrowth of metal single crystals. Revised melt-growth theory should include both the growth and the formation of the regular structure as evidenced by neutron diffraction topography. (author)

Properties of nano-structured Ni/YSZ anodes fabricated from plasma sprayable NiO/YSZ powder prepared by single step solution combustion method

Energy Technology Data Exchange (ETDEWEB)

Prakash, B. Shri; Balaji, N.; Kumar, S. Senthil; Aruna, S.T., E-mail: staruna194@gmail.com

2016-12-15

Highlights: • Preparation of plasma grade NiO/YSZ powder in single step. • Fabrication of nano-structured Ni/YSZ coating. • Conductivity of 600 S/cm at 800 °C. - Abstract: NiO/YSZ anode coatings are fabricated by atmospheric plasma spraying at different plasma powers from plasma grade NiO/YSZ powders that are prepared in a single step by solution combustion method. The process adopted is devoid of multi-steps that are generally involved in conventional spray drying or fusing and crushing methods. Density of the coating increased and porosity decreased with increase in the plasma power of deposition. An ideal nano-structured Ni/YSZ anode encompassing nano YSZ particles, nano Ni particles and nano pores is achieved on reducing the coating deposited at lower plasma powers. The coating exhibit porosities in the range of 27%, sufficient for anode functional layers. Electronic conductivity of the coatings is in the range of 600 S/cm at 800 °C.

Nano-sensing of the orientation of fluorescing molecules with active coated nano-particles

DEFF Research Database (Denmark)

Arslanagic, Samel; Ziolkowski, Richard W.

2015-01-01

The potential of using active coated nano-particles to determine the orientation of fluorescing molecules is reported. By treating each fluorescing molecule as an electric Hertzian dipole, single and multiple fluorescing molecules emitting coherently and incoherently in various orientations...... are considered in the presence of active coated nano-particles. It is demonstrated that in addition to offering a means to determine the orientation of a single molecule or the over-all orientation of the molecules surrounding it, the nature of the far-field response from the active coated nano...

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.

SCAP-82, Single Scattering, Albedo Scattering, Point-Kernel Analysis in Complex Geometry

International Nuclear Information System (INIS)

Disney, R.K.; Vogtman, S.E.

1987-01-01

1 - Description of problem or function: SCAP solves for radiation transport in complex geometries using the single or albedo scatter point kernel method. The program is designed to calculate the neutron or gamma ray radiation level at detector points located within or outside a complex radiation scatter source geometry or a user specified discrete scattering volume. Geometry is describable by zones bounded by intersecting quadratic surfaces within an arbitrary maximum number of boundary surfaces per zone. Anisotropic point sources are describable as pointwise energy dependent distributions of polar angles on a meridian; isotropic point sources may also be specified. The attenuation function for gamma rays is an exponential function on the primary source leg and the scatter leg with a build- up factor approximation to account for multiple scatter on the scat- ter leg. The neutron attenuation function is an exponential function using neutron removal cross sections on the primary source leg and scatter leg. Line or volumetric sources can be represented as a distribution of isotropic point sources, with un-collided line-of-sight attenuation and buildup calculated between each source point and the detector point. 2 - Method of solution: A point kernel method using an anisotropic or isotropic point source representation is used, line-of-sight material attenuation and inverse square spatial attenuation between the source point and scatter points and the scatter points and detector point is employed. A direct summation of individual point source results is obtained. 3 - Restrictions on the complexity of the problem: - The SCAP program is written in complete flexible dimensioning so that no restrictions are imposed on the number of energy groups or geometric zones. The geometric zone description is restricted to zones defined by boundary surfaces defined by the general quadratic equation or one of its degenerate forms. The only restriction in the program is that the total

Soft Sensing of Key State Variables in Fermentation Process Based on Relevance Vector Machine with Hybrid Kernel Function

Directory of Open Access Journals (Sweden)

Xianglin ZHU

2014-06-01

Full Text Available To resolve the online detection difficulty of some important state variables in fermentation process with traditional instruments, a soft sensing modeling method based on relevance vector machine (RVM with a hybrid kernel function is presented. Based on the characteristic analysis of two commonly-used kernel functions, that is, local Gaussian kernel function and global polynomial kernel function, a hybrid kernel function combing merits of Gaussian kernel function and polynomial kernel function is constructed. To design optimal parameters of this kernel function, the particle swarm optimization (PSO algorithm is applied. The proposed modeling method is used to predict the value of cell concentration in the Lysine fermentation process. Simulation results show that the presented hybrid-kernel RVM model has a better accuracy and performance than the single kernel RVM model.

Single-crystal charge transfer interfaces for efficient photonic devices (Conference Presentation)

Science.gov (United States)

Alves, Helena; Pinto, Rui M.; Maçôas, Ermelinda M. S.; Baleizão, Carlos; Santos, Isabel C.

2016-09-01

Organic semiconductors have unique optical, mechanical and electronic properties that can be combined with customized chemical functionality. In the crystalline form, determinant features for electronic applications such as molecular purity, the charge mobility or the exciton diffusion length, reveal a superior performance when compared with materials in a more disordered form. Combining crystals of two different conjugated materials as even enable a new 2D electronic system. However, the use of organic single crystals in devices is still limited to a few applications, such as field-effect transistors. In 2013, we presented the first system composed of single-crystal charge transfer interfaces presenting photoconductivity behaviour. The system composed of rubrene and TCNQ has a responsivity reaching 1 A/W, corresponding to an external quantum efficiency of nearly 100%. A similar approach, with a hybrid structure of a PCBM film and rubrene single crystal also presents high responsivity and the possibility to extract excitons generated in acceptor materials. This strategy led to an extended action towards the near IR. By adequate material design and structural organisation of perylediimides, we demonstrate that is possible to improve exciton diffusion efficiency. More recently, we have successfully used the concept of charge transfer interfaces in phototransistors. These results open the possibility of using organic single-crystal interfaces in photonic applications.

The role of stable interface in nano-sized FeNbO4 as anode electrode for lithium-ion batteries

International Nuclear Information System (INIS)

Wang, Ting; Shi, Shaojun; Kong, Fanjun; Yang, Gang; Qian, Bin; Yin, Fan

2016-01-01

Graphical abstract: After dozens of charge/discharge cycles, the electrode of Nano-FNO remains the homogeneous combination with active material and conductive carbon, but the microcrystals in Micro-FNO electrode are cracked to small particles. The pulverization of Micro-FNO not only blocks the transfer of Li + and electrons due to the separation of the active material and conductive carbon, but also results in the falling of active material from the current collector. Nano-FNO can remain the excellent capacity after dozens of cycles. - Abstract: Nano-sized FeNbO 4 (Nano-FNO) with an average diameter of 120 nm is facilely prepared by co-precipitation method. Bulk FeNbO 4 (Micro-FNO) as a comparison synthesized by conventional solid-state synthesis has an average grain size of 3–10 μm. In the high-resolution transmission electron microscopy (HRTEM) images, Nano-FNO reveals an ordered single crystal structure, but Mirco-FNO is composed of disordered crystallites with different crystal orientation. Nano-FNO as anode material delivers the initial capacity of 475 mAh g −1 which is much higher than Micro-FNO electrode of 250 mAh g −1 .After dozens of charge/discharge cycles, the electrode of Nano-FNO remains the homogeneous combination with active material and conductive carbon, but the microcrystals in Micro-FNO electrode are cracked to small particles. The pulverization of Micro-FNO not only blocks the transfer of Li + and electrons due to the separation between the active material and conductive carbon, but also results in the falling of active material from the current collector. Compared with the weakened electrochemical performances of Micro-FNO, Nano-FNO remains the excellent capacity after dozens of cycles. The charge transfer resistances of Nano-FNO and Micro-FNO after several cycles are further studied by fitting their electrochemical impedance spectra.

Interfacial Interactions and Nano structure Changes in DPPG/HD Monolayer at the Air/Water Interface

International Nuclear Information System (INIS)

Zhu, H.; Zhang, P.; Sun, R.; Hao, Ch.; Wang, J.; Zhu, H.; Zhang, T.; Zhang, P.; Li, Sh.

2015-01-01

Lung surfactant (LS) plays a crucial role in regulating surface tension during normal respiration cycles by decreasing the work associated with lung expansion and therefore decreases the metabolic energy consumed. Monolayer surfactant films composed of a mixture of phospholipids and spreading additives are of optional utility for applications in lung surfactant-based therapies. A simple, minimal model of such a lung surfactant system, composed of 1,2-dipalmitoyl-sn-glycero-3-[phosphor-rac-(1-glycerol)] (DPPG) and hexadecanol (HD), was prepared, and the surface pressure-area π-A) isotherms and nano structure characteristics of the binary mixture were investigated at the air/water interface using a combination of Langmuir-Blodgett (LB) and atomic force microscopy (AFM) techniques. Based on the regular solution theory, the miscibility and stability of the two components in the monolayer were analyzed in terms of compression modulusC_s"-1) , excess Gibbs free energy (δG"π_exc) , activity coefficients (γ), and interaction parameterζ. The results of this paper provide valuable insight into basic thermodynamics and nano structure of mixed DPPG/HD monolayers; it is helpful to understand the thermodynamic behavior of HD as spreading additive in LS monolayer with a view toward characterizing potential improvements to LS performance brought about by addition of HD to lung phospholipids

Natural Language Search Interfaces: Health Data Needs Single-Field Variable Search.

Science.gov (United States)

Jay, Caroline; Harper, Simon; Dunlop, Ian; Smith, Sam; Sufi, Shoaib; Goble, Carole; Buchan, Iain

2016-01-14

Data discovery, particularly the discovery of key variables and their inter-relationships, is key to secondary data analysis, and in-turn, the evolving field of data science. Interface designers have presumed that their users are domain experts, and so they have provided complex interfaces to support these "experts." Such interfaces hark back to a time when searches needed to be accurate first time as there was a high computational cost associated with each search. Our work is part of a governmental research initiative between the medical and social research funding bodies to improve the use of social data in medical research. The cross-disciplinary nature of data science can make no assumptions regarding the domain expertise of a particular scientist, whose interests may intersect multiple domains. Here we consider the common requirement for scientists to seek archived data for secondary analysis. This has more in common with search needs of the "Google generation" than with their single-domain, single-tool forebears. Our study compares a Google-like interface with traditional ways of searching for noncomplex health data in a data archive. Two user interfaces are evaluated for the same set of tasks in extracting data from surveys stored in the UK Data Archive (UKDA). One interface, Web search, is "Google-like," enabling users to browse, search for, and view metadata about study variables, whereas the other, traditional search, has standard multioption user interface. Using a comprehensive set of tasks with 20 volunteers, we found that the Web search interface met data discovery needs and expectations better than the traditional search. A task × interface repeated measures analysis showed a main effect indicating that answers found through the Web search interface were more likely to be correct (F1,19=37.3, Pnatural language search interfaces for variable search supporting in particular: query reformulation; data browsing; faceted search; surrogates; relevance

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice.

Science.gov (United States)

Liu, Jie; Huang, Juan; Guo, Huan; Lan, Liu; Wang, Hongze; Xu, Yuancheng; Yang, Xiaohong; Li, Wenqiang; Tong, Hao; Xiao, Yingjie; Pan, Qingchun; Qiao, Feng; Raihan, Mohammad Sharif; Liu, Haijun; Zhang, Xuehai; Yang, Ning; Wang, Xiaqing; Deng, Min; Jin, Minliang; Zhao, Lijun; Luo, Xin; Zhou, Yang; Li, Xiang; Zhan, Wei; Liu, Nannan; Wang, Hong; Chen, Gengshen; Li, Qing; Yan, Jianbing

2017-10-01

Maize ( Zea mays ) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice ( Oryza sativa ) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1 , a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis ( Arabidopsis thaliana ) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1 ). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis. © 2017 American Society of Plant Biologists. All Rights Reserved.

The Kernel Estimation in Biosystems Engineering

Directory of Open Access Journals (Sweden)

Esperanza Ayuga Téllez

2008-04-01

Full Text Available In many fields of biosystems engineering, it is common to find works in which statistical information is analysed that violates the basic hypotheses necessary for the conventional forecasting methods. For those situations, it is necessary to find alternative methods that allow the statistical analysis considering those infringements. Non-parametric function estimation includes methods that fit a target function locally, using data from a small neighbourhood of the point. Weak assumptions, such as continuity and differentiability of the target function, are rather used than "a priori" assumption of the global target function shape (e.g., linear or quadratic. In this paper a few basic rules of decision are enunciated, for the application of the non-parametric estimation method. These statistical rules set up the first step to build an interface usermethod for the consistent application of kernel estimation for not expert users. To reach this aim, univariate and multivariate estimation methods and density function were analysed, as well as regression estimators. In some cases the models to be applied in different situations, based on simulations, were defined. Different biosystems engineering applications of the kernel estimation are also analysed in this review.

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

Design and fabrication of single-crystal GaN nano-bridge on homogeneous substrate for nanoindentation

Science.gov (United States)

Hung, Shang-Chao

2014-12-01

This study reports a simple method to design and fabricate a freestanding GaN nano-bridge over a homogeneous short column as supporting leg. Test samples were fabricated from MOCVD-grown single-crystal GaN films over sapphire substrate using a FIB milling to leave freestanding short spans. We also investigated the nanoindentation characteristics and the corresponding nanoscopic mechanism of the GaN nano-bridge and its short column with a conical indenter inside transmission electron microscopy. The stress-strain mechanical properties and Young's modulus have also been examined and calculated as 108 GPa ± 4.8 % by the strain energy method. The significant slope switch of the L- D curve corresponds to the transition from the single-point bending indentation to the surface stretching indentation and has been interpreted with the evolution of TEM images. This freestanding fabrication and test have key advantages to characterize nanoscale behavior of one-dimensional bridge structure and greater ease of sample preparation over other micro-fabrication techniques.

[Effect of nano-hydroxyapatite to glass ionomer cement].

Science.gov (United States)

Mu, Ya-Bing; Zang, Guang-Xiang; Sun, Hong-Chen; Wang, Cheng-Kun

2007-12-01

To investigate the mechanical character, microleakage and mineralizing potential of nano-hydroxyapatite (nano-HAP)-added glass ionomer cement(GIC). 8% nano-HAP were incorporated into GIC as composite, and pure GIC as control. Both types of material were used to make 20 cylinders respectively in order to detect three-point flexural strength and compressive strength. Class V cavities were prepared in 120 molars extracted for orthodontic treatment, then were filled by two kinds of material. The microleakage at the composite-dentine interface was observed with confocal laser scanning microscope (CLSM) after stained with 1% rhodamin-B-isothiocyanate for 24 hours. Class V cavities were prepared in the molars of 4 healthy dogs, filled with composite, and the same molars in the other side were filled with GIC as control. The teeth were extracted to observe the mineralizing property with polarimetric microscope in 8 weeks after filling. Three-point flexural strength and compressive of nano-HAP-added GIC were increased compared with pure GIC (P nano-HAP-added GIC, while there was no hydroxyapatite crystals formed at the interface of tooth and pure GIC. 8% nano-HAP-added GIC can tightly fill tooth and have mineralizing potential, and can be used as liner or filling material for prevention.

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.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

Directory of Open Access Journals (Sweden)

Chunmei Liu

2016-01-01

Full Text Available This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour.

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

Science.gov (United States)

2016-01-01

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour. PMID:27379165

Nano-optical observation of cascade switching in a parallel superconducting nanowire single photon detector

International Nuclear Information System (INIS)

Heath, Robert M.; Tanner, Michael G.; Casaburi, Alessandro; Hadfield, Robert H.; Webster, Mark G.; San Emeterio Alvarez, Lara; Jiang, Weitao; Barber, Zoe H.; Warburton, Richard J.

2014-01-01

The device physics of parallel-wire superconducting nanowire single photon detectors is based on a cascade process. Using nano-optical techniques and a parallel wire device with spatially separate pixels, we explicitly demonstrate the single- and multi-photon triggering regimes. We develop a model for describing efficiency of a detector operating in the arm-trigger regime. We investigate the timing response of the detector when illuminating a single pixel and two pixels. We see a change in the active area of the detector between the two regimes and find the two-pixel trigger regime to have a faster timing response than the one-pixel regime

7 CFR 981.7 - Edible kernel.

Science.gov (United States)

2010-01-01

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

A 3D graphene interface (Si-doped) of Ag matrix with excellent electronic transmission and thermal conductivity via nano-assembly modification

Science.gov (United States)

Ye, Xianzhu; Li, Ming; Zhang, Yafei

2018-04-01

The wide development of electronic materials requires higher load capacity and high temperature resistance. In this study, a novel architecture was fabricated consisting of a 3D reduced graphene oxide (rGO)-Si interface using a simple nano-assembly sintering to achieve high current capacity and excellent thermal features. Via the analysis of catalytic oxidation for methanol, the loading catalytic activity of nano-Ag still remained to a certain extent for the composite with 0.8 vol.% rGO. The final Ag-rGO composite apparently possesses a higher initial oxidation temperature and lower rate of oxidation for internal passing and shielding, and the thermal conductivity is significantly enhanced from 344 to 407 W m‑1 K‑1. Importantly, with a 3D synergistic transportation network, the resistivity of the Ag-rGO composite is much lower than pure Ag, and with a longer conductive time under a stress condition of current density of 6.0  ×  104 A cm‑2. Thermal-electronic features demonstrate that the dispersed graphene interface can efficiently suppress the primary failure pathways (high temperature) in Ag matrix and make it uniquely efficient for the advancement of microscale and thermal-management electronics.

Probing properties, stability, and performances of hierarchical meso-porous materials with nano-scale interfaces

International Nuclear Information System (INIS)

Baldinozzi, Gianguido; Gosset, Dominique; Simeone, David; Muller, Guillaume; Laberty-Robert, Christel; Sanchez, Clement

2012-01-01

Nano-crystals growth mechanism embedded into meso-porous thin films has been determined directly from grazing incidence X-ray diffraction data. We have shown, for the first time, that surface capillary forces control the growth mechanism of nano-crystals into these nano-architectures. Moreover, these data allow an estimation of the surface tension of the nano-crystals organized into a 3-D nano-architecture. The analysis of the variations in the strain field of these nano-crystals gives information on the evolution of the microstructure of these meso-porous films, that is, the contacts among nano-crystals. This work represents the first application of grazing incidence X-ray for understanding stability and performances of meso-porous thin films. This approach can be used to understand the structural stability of these nano-architectures at high temperature. (authors)

Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Directory of Open Access Journals (Sweden)

Hailun Wang

2017-01-01

Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

Kernel versions of some orthogonal transformations

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

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

Model Selection in Kernel Ridge Regression

DEFF Research Database (Denmark)

Exterkate, Peter

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

Penetuan Bilangan Iodin pada Hydrogenated Palm Kernel Oil (HPKO) dan Refined Bleached Deodorized Palm Kernel Oil (RBDPKO)

OpenAIRE

Sitompul, Monica Angelina

2015-01-01

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

7 CFR 981.8 - Inedible kernel.

Science.gov (United States)

2010-01-01

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

Cubic-to-Tetragonal Phase Transitions in Ag-Cu Nano rods

International Nuclear Information System (INIS)

Delogu, F.; Mascia, M.

2012-01-01

Molecular dynamics simulations have been used to investigate the structural behavior of nano rods with square cross section. The nano rods consist of pure Ag and Cu phases or of three Ag and Cu domains in the sequence Ag-Cu-Ag or Cu-Ag-Cu. Ag and Cu domains are separated by coherent interfaces. Depending on the side length and the size of individual domains, Ag and Cu can undergo a transition from the usual face-centered cubic structure to a body-centered tetragonal one. Such transition can involve the whole nano rod, or only the Ag domains. In the latter case, the transition is accompanied by a loss of coherency at the Ag-Cu interfaces, with a consequent release of elastic energy. The observed behaviors are connected with the stresses developed at the nano rod surfaces.

Ledges and grooves at γ/γ′ interfaces of single crystal superalloys

Czech Academy of Sciences Publication Activity Database

Parsa, A. B.; Wollgramm, P.; Buck, H.; Kostka, A.; Somsen, C.; Dlouhý, Antonín; Eggeler, G.

2015-01-01

Roč. 90, MAY (2015), s. 105-117 ISSN 1359-6454 R&D Projects: GA ČR(CZ) GA14-22834S Institutional support: RVO:68081723 Keywords : Ni-base single crystal superalloys * γ/γ′ interfaces * Interface dislocations * Rafting * Grooves Subject RIV: JG - Metallurgy Impact factor: 5.058, year: 2015

7 CFR 981.408 - Inedible kernel.

Science.gov (United States)

2010-01-01

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

Model selection in kernel ridge regression

DEFF Research Database (Denmark)

Exterkate, Peter

2013-01-01

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

Natural Language Search Interfaces: Health Data Needs Single-Field Variable Search

Science.gov (United States)

Smith, Sam; Sufi, Shoaib; Goble, Carole; Buchan, Iain

2016-01-01

Background Data discovery, particularly the discovery of key variables and their inter-relationships, is key to secondary data analysis, and in-turn, the evolving field of data science. Interface designers have presumed that their users are domain experts, and so they have provided complex interfaces to support these “experts.” Such interfaces hark back to a time when searches needed to be accurate first time as there was a high computational cost associated with each search. Our work is part of a governmental research initiative between the medical and social research funding bodies to improve the use of social data in medical research. Objective The cross-disciplinary nature of data science can make no assumptions regarding the domain expertise of a particular scientist, whose interests may intersect multiple domains. Here we consider the common requirement for scientists to seek archived data for secondary analysis. This has more in common with search needs of the “Google generation” than with their single-domain, single-tool forebears. Our study compares a Google-like interface with traditional ways of searching for noncomplex health data in a data archive. Methods Two user interfaces are evaluated for the same set of tasks in extracting data from surveys stored in the UK Data Archive (UKDA). One interface, Web search, is “Google-like,” enabling users to browse, search for, and view metadata about study variables, whereas the other, traditional search, has standard multioption user interface. Results Using a comprehensive set of tasks with 20 volunteers, we found that the Web search interface met data discovery needs and expectations better than the traditional search. A task × interface repeated measures analysis showed a main effect indicating that answers found through the Web search interface were more likely to be correct (F 1,19=37.3, Peffect of task (F 3,57=6.3, Pinterface (F 1,19=18.0, Peffect of task (F 2,38=4.1, P=.025, Greenhouse

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

Science.gov (United States)

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

2018-05-07

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

Viscosity kernel of molecular fluids

DEFF Research Database (Denmark)

Puscasu, Ruslan; Todd, Billy; Daivis, Peter

2010-01-01

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

Kernel learning algorithms for face recognition

CERN Document Server

Li, Jun-Bao; Pan, Jeng-Shyang

2013-01-01

Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

Activity of microemulsion-based nanoparticles at the human bio-nano interface: concentration-dependent effects on thrombosis and hemolysis in whole blood

International Nuclear Information System (INIS)

Morey, Timothy E.; Varshney, Manoj; Flint, Jason A.; Seubert, Christoph N.; Smith, W. Brit; Bjoraker, David G.; Shah, Dinesh O.; Dennis, Donn M.

2004-01-01

Background: Although microemulsion-based nanoparticles (MEs) may be useful for drug delivery or scavenging, these benefits must be balanced against potential nanotoxicological effects in biological tissue (bio-nano interface). We investigated the actions of assembled MEs and their individual components at the bio-nano interface of thrombosis and hemolysis in human blood.Methods: Oil-in-water MEs were synthesized using ethylbutyrate, sodium caprylate, and pluronic F-68 (ME4) or F-127 (ME6) in 0.9% NaCl w/v . The effects of MEs or components on thrombosis were determined using thrombo-elastography, platelet contractile force, clot elastic modulus, and platelet counting. For hemolysis, ME or components were incubated with erythrocytes, centrifuged, and washed for measurement of free hemoglobin by spectroscopy.Results and conclusions: The mean particle diameters (polydispersity index) for ME6 and ME4 were 23.6 ± 2.5 nm (0.362) and 14.0 ± 1.0 nm (0.008), respectively. MEs (0, 0.03, 0.3, 3 mM) markedly reduced the thromboelastograph maximal amplitude in a concentration-dependent manner (49.0 ± 4.2, 39.0 ± 5.6, 15.0 ± 8.7, 3.8 ± 1.3 mm, respectively), an effect highly correlated (r2 = 0.94) with similar changes caused by pluronic surfactants (48.7 ± 10.9, 30.7 ± 15.8, 20.0 ± 11.3, 2.0 ± 0.5) alone. Neither oil nor sodium caprylate alone affected the thromboelastograph. The clot contractile force was reduced by ME (27.3 ± 11.1-6.7 ± 3.4 kdynes/cm 2 , P = 0.02, n = 5) whereas the platelet population not affected (175 ± 28-182 ± 23 10 6 /ml, P = 0.12, n = 6). This data suggests that MEs reduced platelet activity due to associated pluronic surfactants, but caused minimal changes in protein function necessary for coagulation. Although pharmacological concentrations of sodium caprylate caused hemolysis (EC 50 = 213 mM), MEs and pluronic surfactants did not disrupt erythrocytes. Knowledge of nanoparticle activity and potential associated nanotoxicity at this bio-nano

Activity of microemulsion-based nanoparticles at the human bio-nano interface: concentration-dependent effects on thrombosis and hemolysis in whole blood

Energy Technology Data Exchange (ETDEWEB)

Morey, Timothy E.; Varshney, Manoj; Flint, Jason A.; Seubert, Christoph N.; Smith, W. Brit; Bjoraker, David G.; Shah, Dinesh O.; Dennis, Donn M. [University of Florida, Departments of Anesthesiology, Chemical Engineering, and Pharmacology and Experimental Therapeutics, Engineering Research Center for Particle Science and Technology (United States)], E-mail: DDennis@ufl.edu

2004-06-15

Background: Although microemulsion-based nanoparticles (MEs) may be useful for drug delivery or scavenging, these benefits must be balanced against potential nanotoxicological effects in biological tissue (bio-nano interface). We investigated the actions of assembled MEs and their individual components at the bio-nano interface of thrombosis and hemolysis in human blood.Methods: Oil-in-water MEs were synthesized using ethylbutyrate, sodium caprylate, and pluronic F-68 (ME4) or F-127 (ME6) in 0.9% NaCl{sub w/v}. The effects of MEs or components on thrombosis were determined using thrombo-elastography, platelet contractile force, clot elastic modulus, and platelet counting. For hemolysis, ME or components were incubated with erythrocytes, centrifuged, and washed for measurement of free hemoglobin by spectroscopy.Results and conclusions: The mean particle diameters (polydispersity index) for ME6 and ME4 were 23.6 {+-} 2.5 nm (0.362) and 14.0 {+-} 1.0 nm (0.008), respectively. MEs (0, 0.03, 0.3, 3 mM) markedly reduced the thromboelastograph maximal amplitude in a concentration-dependent manner (49.0 {+-} 4.2, 39.0 {+-} 5.6, 15.0 {+-} 8.7, 3.8 {+-} 1.3 mm, respectively), an effect highly correlated (r2 = 0.94) with similar changes caused by pluronic surfactants (48.7 {+-} 10.9, 30.7 {+-} 15.8, 20.0 {+-} 11.3, 2.0 {+-} 0.5) alone. Neither oil nor sodium caprylate alone affected the thromboelastograph. The clot contractile force was reduced by ME (27.3 {+-} 11.1-6.7 {+-} 3.4 kdynes/cm{sup 2}, P = 0.02, n = 5) whereas the platelet population not affected (175 {+-} 28-182 {+-} 23 10{sup 6}/ml, P = 0.12, n = 6). This data suggests that MEs reduced platelet activity due to associated pluronic surfactants, but caused minimal changes in protein function necessary for coagulation. Although pharmacological concentrations of sodium caprylate caused hemolysis (EC{sub 50} = 213 mM), MEs and pluronic surfactants did not disrupt erythrocytes. Knowledge of nanoparticle activity and

Partial Deconvolution with Inaccurate Blur Kernel.

Science.gov (United States)

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

2017-10-17

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

Kernel methods for deep learning

OpenAIRE

Cho, Youngmin

2012-01-01

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

Study on the coherence degree of magnetization reversal in Permalloy single-domain nano-ellipses

Energy Technology Data Exchange (ETDEWEB)

Júnior, D.S. Vieira [Departamento Acadêmico de Matemática, Física, e Estatística, Instituto Federal de Educação, Ciência e Tecnologia do Sudeste de Minas Gerais – Campus Rio Pomba, Rio Pomba, Minas Gerais 36180-000 (Brazil); Leonel, S.A. [Departamento de Física, Laboratório de Simulação Computacional, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais 36036-330 (Brazil); Toscano, D., E-mail: danilotoscano@fisica.ufjf.br [Departamento de Física, Laboratório de Simulação Computacional, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais 36036-330 (Brazil); Sato, F.; Coura, P.Z.; Dias, R.A. [Departamento de Física, Laboratório de Simulação Computacional, Universidade Federal de Juiz de Fora, Juiz de Fora, Minas Gerais 36036-330 (Brazil)

2017-03-15

Numerical simulations have been performed to study the magnetization reversal in Permalloy nano-ellipses, under combined in-plane magnetic fields along the longitudinal and the transverse directions. We have considered nano-ellipses with two different aspect ratios and five thicknesses: 220×80×t nm{sup 3} and 70×50×t nm{sup 3}, where t ranging from 5 to 25 nm in steps of 5 nm. We found that the mechanism of magnetization reversal is not only dependent on the parameters of the magnetic field pulse but also related to the ellipse dimensions. It is known that the reversal time is related to the mechanism behind the magnetization reversal. In particular, ultrafast magnetization reversals occur by coherent rotation, when applying a field oriented mainly perpendicular to the initial magnetization. In order to evaluate the degree of coherence of the magnetization reversal we have introduced a quantity called “coherence index”. Besides complementing the previous studies by including the effect of the thickness on the magnetization reversal, our results indicate that it is possible to obtain magnetization reversals with high degree of coherence in small nano-ellipses by adjusting the geometric factors of the ellipse and the parameters of the magnetic field pulse simultaneously. - Highlights: • Magnetization reversals in single-domain nano-ellipses were investigated. • A parameter to evaluate the degree of coherence of the magnetization reversal was proposed. • A higher coherence index indicates a complete, coherent, rotation of the magnetization.

Optimizing memory-bound SYMV kernel on GPU hardware accelerators

KAUST Repository

Abdelfattah, Ahmad

2013-01-01

Hardware accelerators are becoming ubiquitous high performance scientific computing. They are capable of delivering an unprecedented level of concurrent execution contexts. High-level programming language extensions (e.g., CUDA), profiling tools (e.g., PAPI-CUDA, CUDA Profiler) are paramount to improve productivity, while effectively exploiting the underlying hardware. We present an optimized numerical kernel for computing the symmetric matrix-vector product on nVidia Fermi GPUs. Due to its inherent memory-bound nature, this kernel is very critical in the tridiagonalization of a symmetric dense matrix, which is a preprocessing step to calculate the eigenpairs. Using a novel design to address the irregular memory accesses by hiding latency and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double precision arithmetics, respectively. © 2013 Springer-Verlag.

The influence of orientation and practical size on the interface fracture of a bone-nano composite cement

International Nuclear Information System (INIS)

Ilik, Igor; Khandaker, Morshed

2010-01-01

Clinical follow-up studies in cemented total hip arthroplasties found that femoral prosthesis loosening is caused by the fracture of the bone-cement interfaces. The research objectives were to determine whether orientation of the bone has any influence on the interface fracture strength, and to determine whether inclusion of micro/nano sizes MgO particles on Cobalt HV bone cement has any influence on the interface fracture strength. Flexural tests were conducted on five groups of specimens to find Young Modulus and bending strength: (1) longitudinal bone, (2) transverse bone, (3) pure cement particles, (4) cement with 36 im and 27 nm MgO particles, and (5) cement with 27nm MgO particles. Also, fracture tests were conducted on six groups of bone-cement specimen to find interface fracture toughness: (1) longitudinal bone-cement without MgO particles, (2) transverse bone-cement without MgO particles, (3) longitudinal bone-cement with 36 im MgO particles, (4) transverse bone-cement with 36 im MgO particles, (5) , longitudinal bone-cement with 27 nm MgO particles, and (6) transverse bone-cement with 27 nm MgO particles. Transverse bone specimen was 14% stiffer than longitudinal specimen, while bending strength and fracture toughness of longitudinal specimen was 29% and 2.6 times lower than the transverse specimen, respectively. Reduction of Young's modulus (7.3%), bending strength (27%) and fracture toughness (16%) was observed by the inclusion of microsize MgO particles, and a reduction of the Young's Modulus (19%), bending strength (21%),and fracture toughness (19%) for nanosize MgO particles. The interface toughness of the transverse bone infused with 27nm MgO was about 6 times higher than transverse bone infused with 36 im particles of MgO. Preliminary studies show that orientation of the bone has significant influence on the interface fracture. MgO particles size have a significant effect on the strength of the bone - cement interface.(Author)

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...

Thermal formation of mesoporous single-crystal Co3O4 nano-needles and their lithium storage properties

KAUST Repository

Lou, Xiong Wen; Deng, Da; Lee, Jim Yang; Archer, Lynden A.

2008-01-01

In this work, we report the simple solid-state formation of mesoporous Co3O4 nano-needles with a 3D single-crystalline framework. The synthesis is based on controlled thermal oxidative decomposition and re-crystallization of precursor β-Co(OH)2 nano-needles. Importantly, after thermal treatment, the needle-like morphology can be completely preserved, despite the fact that there is a large volume contraction accompanying the process: β-Co(OH)2 → Co3O 4. Because of the intrinsic crystal contraction, a highly mesoporous structure with high specific surface area has been simultaneously created. The textual properties can be easily tailored by varying the annealing temperature between 200-400 °C. Interestingly, thermal re-crystallization at higher temperatures leads to the formation of a perfect 3D single-crystalline framework. Thus derived mesoporous Co3O4 nano-needles serve as a good model system for the study of lithium storage properties. The optimized sample manifests very low initial irreversible loss (21%), ultrahigh capacity, and excellent cycling performance. For example, a reversible capacity of 1079 mA h g-1 can be maintained after 50 cycles. The superior electrochemical performance and ease of synthesis may suggest their practical use in lithium-ion batteries. © The Royal Society of Chemistry 2008.

Migrating Multi-page Web Applications to Single-page AJAX Interfaces

NARCIS (Netherlands)

Mesbah, A.; Van Deursen, A.

2006-01-01

Recently, a new web development technique for creating interactive web applications, dubbed AJAX, has emerged. In this new model, the single-page web interface is composed of individual components which can be updated/replaced independently. With the rise of AJAX web applications classical

MDI: Mathematica database interface for the MFEDB

International Nuclear Information System (INIS)

Wiley, J.C.; Miner, W.H. Jr.; Ross, D.W.

1992-04-01

We describe a new interface for the Magnetic Fusion Energy Database, MFEDB, which uses Mathematica reg-sign as a front end. MDI is a Mathematica package that defines a basic set of MFEDB access functions. The package will also accept standard SQL queries. Each function returns Mathematica-style lists, which can then be manipulated with any of the Mathematica functions. MDI also provides some utility functions for plotting and analyzing the data. The MDI package essentially makes the MFEDB an extension of Mathematica. The user may use any of the many Mathematica front-ends including telnet, X-Windows, or a notebook. The mdi.m package may be obtained by anonymous FTP from the MFEDB site or by use of netmfe, and E-mail database interface. MDI is a example of distributed computing. Behind the user interface, MDI calls an RPC client program that communicates with an RPC server on the MFEDB computer. It relies on the network communication capabilities of Mathematica to connect the user to a workstation running the Mathematica kernel. The Mathematica kernel is then connected to the MFEDB host workstation by a client/server pair of RPC processes. If the Mathematica kernel is to be run on the users' machine, the RPC client program must also be obtained and installed. The MDI RPC server is also available for users who would like to provide their own client software. The server returns ASCII tables from standards queries and may be accessed and processed by any program on the internet that has access to RPC services

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. ...

Development of nano SiO2 incorporated nano zinc phosphate coatings on mild steel

International Nuclear Information System (INIS)

Tamilselvi, M.; Kamaraj, P.; Arthanareeswari, M.; Devikala, S.; Selvi, J. Arockia

2015-01-01

Highlights: • Nano SiO 2 incorporated nano zinc phosphate coating on mild steel was developed. • Coatings showed enhanced corrosion resistance. • The nano SiO 2 is adsorbed on mild steel surface and become nucleation sites. • The nano SiO 2 accelerates the phosphating process. - Abstract: This paper reports the development of nano SiO 2 incorporated nano zinc phosphate coatings on mild steel at low temperature for achieving better corrosion protection. A new formulation of phosphating bath at low temperature with nano SiO 2 was attempted to explore the possibilities of development of nano zinc phosphate coatings on mild steel with improved corrosion resistance. The coatings developed were studied by Scanning Electron Microscopy (SEM), Energy-Dispersive X-ray Spectroscopy (EDX), X-ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and Electrochemical measurements. Significant variation in the coating weight, morphology and corrosion resistance was observed as nano SiO 2 concentrations varied from 0.5–4 g/L. The results showed that, the nano SiO 2 in the phosphating solution changed the initial potential of the interface between mild steel substrate and phosphating solution and reduce the activation energy of the phosphating process, increase the nucleation sites and yielded zinc phosphate coatings of higher coating weight, greater surface coverage and enhanced corrosion resistance. Better corrosion resistance was observed for coatings derived from phosphating bath containing 1.5 g/L nano SiO 2 . The new formulation reported in the present study was free from Ni or Mn salts and had very low concentration of sodium nitrite (0.4 g/L) as accelerator

Cancer Nano medicine

International Nuclear Information System (INIS)

Li, H.; Pike, M.M.; Luo, X.; Liu, L.H.

2013-01-01

Bioengineered nano materials have inspired revolutionary imaging and drug delivery methods whose clinical application in cancer research has resulted in powerful medical devices for early diagnosis, treatment, and prevention of cancer. Recent advances in super imaging agents have resulted in improved resolution and sensitivity. For instance, fluorescent quantum dots with wavelength-tunable emissions, plasmon-resonant gold nano structures with shape-controlled near-infrared absorptions, and MRI-active iron oxide nanoparticles are well-established molecular imaging probes for noninvasive cancer imaging. Nano materials are also considered to be the most effective vectors that can break through transport bio barriers and deliver a constant dose of multiple therapeutic agents to tumors and intracellular endocytic compartments for cancer gene therapy, immunotherapy, or chemotherapy. Furthermore, nano wire- or nano tube-based electronic devices demonstrate extraordinary sensitivity capable of detection at the single molecule or protein level. It is anticipated that developing nano technology-driven imaging, sensing, and therapeutic systems will dramatically advance cancer research and clinical treatments.

Manipulation and functionalization of nano-tubes: application to boron nitride nano-tubes

International Nuclear Information System (INIS)

Maguer, A.

2007-01-01

This PhD work is divided into two parts dealing with boron nitride (BNNT) and carbon nano-tubes. The first part is about synthesis, purification and chemical functionalization of BNNT. Single-walled BNNT are synthesized by LASER ablation of a hBN target. Improving the synthesis parameters first allowed us to limit the byproducts (hBN, boric acid). A specific purification process was then developed in order to enrich the samples in nano-tubes. Purified samples were then used to develop two new chemical functionalization methods. They both involve chemical molecules that present a high affinity towards the BN network. The use of long chain-substituted quinuclidines and borazines actually allowed the solubilization of BNNT in organic media. Purification and functionalization were developed for single-walled BNNT and were successfully applied to multi-walled BNNT. Sensibility of boron to thermic neutrons finally gave birth to a study about covalent functionalization possibilities of the network. The second part of the PhD work deals with separation of carbon nano-tubes depending on their properties. Microwave irradiation of carbon nano-tubes first allowed the enrichment of initially polydisperse samples in large diameter nano-tubes. A second strategy involving selective interaction between one type of tubes and fullerene micelles was finally envisaged to selectively solubilize carbon nano-tubes with specific electronic properties. (author) [fr

An Approximate Approach to Automatic Kernel Selection.

Science.gov (United States)

Ding, Lizhong; Liao, Shizhong

2016-02-02

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

Iterative software kernels

Energy Technology Data Exchange (ETDEWEB)

Duff, I.

1994-12-31

This workshop focuses on kernels for iterative software packages. Specifically, the three speakers discuss various aspects of sparse BLAS kernels. Their topics are: `Current status of user lever sparse BLAS`; Current status of the sparse BLAS toolkit`; and `Adding matrix-matrix and matrix-matrix-matrix multiply to the sparse BLAS toolkit`.

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

Science.gov (United States)

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

2018-05-01

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

A kernel version of spatial factor analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

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

Optimizing memory-bound SYMV kernel on GPU hardware accelerators

KAUST Repository

Abdelfattah, Ahmad; Dongarra, Jack; Keyes, David E.; Ltaief, Hatem

2013-01-01

and increasing bandwidth, our preliminary asymptotic results show 3.5x and 2.5x fold speedups over the similar CUBLAS 4.0 kernel, and 7-8% and 30% fold improvement over the Matrix Algebra on GPU and Multicore Architectures (MAGMA) library in single and double

Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

Science.gov (United States)

Karmeshu; Gupta, Varun; Kadambari, K V

2011-06-01

A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

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...

Composite population kernels in ytterbium-buffer collisions studied by means of laser-saturated absorption

International Nuclear Information System (INIS)

Zhu, X.

1986-01-01

We present a systematic study of composite population kernels for 174 Yb collisions with He, Ar, and Xe buffer gases, using laser-saturation spectroscopy. 174 Yb is chosen as the active species because of the simple structure of its 1 S 0 - 3 P 1 resonance transition (lambda = 556 nm). Elastic collisions are modeled by means of a composite collision kernel, an expression of which is explicitly derived based on arguments of a hard-sphere potential and two-category collisions. The corresponding coupled population-rate equations are solved by iteration to obtain an expression for the saturated-absorption line shape. This expression is fit to the data to obtain information about the composite kernel, along with reasonable values for other parameters. The results confirm that a composite kernel is more general and realistic than a single-component kernel, and the generality in principle and the practical necessity of the former are discussed

Single fiber push-out characterization of interfacial mechanical properties in unidirectional CVI-C/SiC composites by the nano-indentation technique

Science.gov (United States)

Zhang, Lifeng; Ren, Chengzu; Zhou, Changling; Xu, Hongzhao; Jin, Xinmin

2015-12-01

The characterization of interfaces in woven ceramic matrix composites is one of the most challenging problems in composite application. In this investigation, a new model material consisting of the chemical vapor infiltration unidirectional C/SiC composites with PyC fiber coating were prepared and evaluated to predict the interfacial mechanic properties of woven composites. Single fiber push-out/push-back tests with the Berkovich indenter were conducted on the thin sliced specimens using nano-indentation technique. To give a detailed illustration of the interfacial crack propagation and failure mechanism, each sector during the push-out process was analyzed at length. The test results show that there is no detectable difference between testing a fiber in a direct vicinity to an already tested fiber and testing a fiber in vicinity to not-pushed fibers. Moreover, the interface debonding and fiber sliding mainly occur at the PyC coating, and both the fiber and surrounding matrix have no plastic deformation throughout the process. Obtained from the load-displacement curve, the interfacial debonding strength (IDS) and friction stress (IFS) amount to, respectively, 35 ± 5 MPa and 10 ± 1 MPa. Based on the findings, the interfacial properties with PyC fiber coating can be predicted. Furthermore, it is expected to provide a useful guideline for the design, evaluation and optimal application of CVI-C/SiC.

Method for calculating anisotropic neutron transport using scattering kernel without polynomial expansion

International Nuclear Information System (INIS)

Takahashi, Akito; Yamamoto, Junji; Ebisuya, Mituo; Sumita, Kenji

1979-01-01

A new method for calculating the anisotropic neutron transport is proposed for the angular spectral analysis of D-T fusion reactor neutronics. The method is based on the transport equation with new type of anisotropic scattering kernels formulated by a single function I sub(i) (μ', μ) instead of polynomial expansion, for instance, Legendre polynomials. In the calculation of angular flux spectra by using scattering kernels with the Legendre polynomial expansion, we often observe the oscillation with negative flux. But in principle this oscillation disappears by this new method. In this work, we discussed anisotropic scattering kernels of the elastic scattering and the inelastic scatterings which excite discrete energy levels. The other scatterings were included in isotropic scattering kernels. An approximation method, with use of the first collision source written by the I sub(i) (μ', μ) function, was introduced to attenuate the ''oscillations'' when we are obliged to use the scattering kernels with the Legendre polynomial expansion. Calculated results with this approximation showed remarkable improvement for the analysis of the angular flux spectra in a slab system of lithium metal with the D-T neutron source. (author)

Transferring metallic nano-island on hydrogen passivated silicon surface for nano-electronics

International Nuclear Information System (INIS)

Deng, J; Troadec, C; Joachim, C

2009-01-01

In a planar configuration, precise positioning of ultra-flat metallic nano-islands on semiconductor surface opens a way to construct nanostructures for atomic scale interconnects. Regular triangular Au nano-islands have been grown on atomically flat MoS 2 substrates and manipulated by STM to form nanometer gap metal-pads connector for single molecule electronics study. The direct assembly of regular shaped metal nano-islands on H-Si(100) is not achievable. Here we present how to transfer Au triangle nano-islands from MoS 2 onto H-Si(100) in a clean manner. In this experiment, clean MoS 2 substrates are patterned as array of MoS 2 pillars with height of 8 μm. The Au triangle nano-islands are grown on top of the pillars. Successful printing transfer of these Au nano-islands from the MoS 2 pillars to the H-Si(100) is demonstrated.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

Science.gov (United States)

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

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…

Subsurface defects structural evolution in nano-cutting of single crystal copper

International Nuclear Information System (INIS)

Wang, Quanlong; Bai, Qingshun; Chen, Jiaxuan; Sun, Yazhou; Guo, Yongbo; Liang, Yingchun

2015-01-01

Highlights: • An innovative analysis method is adopted to analyze nano-cutting process accurately. • A characteristic SFT and stair-rod dislocation are found in subsurface defect layer. • The formation mechanism of stair-rod dislocation is investigated. • The local atomic structure of subsurface defects is introduced. - Abstract: In this work, molecular dynamics simulation is performed to study the subsurface defects structural distribution and its evolution during nano-cutting process of single crystal copper. The formation mechanism of chip and machined surface is interviewed by analyzing the dislocation evolution and atomic migration. The centro-symmetry parameter and spherical harmonics method are adopted to characterize the distribution and evolution of the subsurface defect structures and local atomic structures. The results show that stacking faults, dislocation loops, “V-shaped” dislocation loops, and plenty of point defects are formed during the machined surface being formed in shear-slip zone. In subsurface damage layers, stair-rod dislocation, stacking fault tetrahedra, atomic cluster defect, and vacancy defect are formed. And the formation mechanism of stair-rod dislocation is investigated by atomic-scale structure evolution. The local atomic structures of subsurface defects are icosahedrons, hexagonal close packed, body-centered cubic, and defect face center cubic, and the variations of local atomic structures are investigated

Subsurface defects structural evolution in nano-cutting of single crystal copper

Energy Technology Data Exchange (ETDEWEB)

Wang, Quanlong [School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001 (China); Center for Precision Engineering, Harbin Institute of Technology, Harbin 150001 (China); Bai, Qingshun [School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001 (China); Chen, Jiaxuan, E-mail: wangquanlong0@hit.edu.cn [Center for Precision Engineering, Harbin Institute of Technology, Harbin 150001 (China); Sun, Yazhou [School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001 (China); Guo, Yongbo [Center for Precision Engineering, Harbin Institute of Technology, Harbin 150001 (China); Liang, Yingchun [School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001 (China)

2015-07-30

Highlights: • An innovative analysis method is adopted to analyze nano-cutting process accurately. • A characteristic SFT and stair-rod dislocation are found in subsurface defect layer. • The formation mechanism of stair-rod dislocation is investigated. • The local atomic structure of subsurface defects is introduced. - Abstract: In this work, molecular dynamics simulation is performed to study the subsurface defects structural distribution and its evolution during nano-cutting process of single crystal copper. The formation mechanism of chip and machined surface is interviewed by analyzing the dislocation evolution and atomic migration. The centro-symmetry parameter and spherical harmonics method are adopted to characterize the distribution and evolution of the subsurface defect structures and local atomic structures. The results show that stacking faults, dislocation loops, “V-shaped” dislocation loops, and plenty of point defects are formed during the machined surface being formed in shear-slip zone. In subsurface damage layers, stair-rod dislocation, stacking fault tetrahedra, atomic cluster defect, and vacancy defect are formed. And the formation mechanism of stair-rod dislocation is investigated by atomic-scale structure evolution. The local atomic structures of subsurface defects are icosahedrons, hexagonal close packed, body-centered cubic, and defect face center cubic, and the variations of local atomic structures are investigated.

Characterisation and final disposal behaviour of theoria-based fuel kernels in aqueous phases

International Nuclear Information System (INIS)

Titov, M.

2005-08-01

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

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.

Towards strong light-matter coupling at the single-resonator level with sub-wavelength mid-infrared nano-antennas

Energy Technology Data Exchange (ETDEWEB)

Malerba, M.; De Angelis, F., E-mail: francesco.deangelis@iit.it [Istituto Italiano di Tecnologia, Via Morego, 30, I-16163 Genova (Italy); Ongarello, T.; Paulillo, B.; Manceau, J.-M.; Beaudoin, G.; Sagnes, I.; Colombelli, R., E-mail: raffaele.colombelli@u-psud.fr [Centre for Nanoscience and Nanotechnology (C2N Orsay), CNRS UMR9001, Univ. Paris Sud, Univ. Paris Saclay, 91405 Orsay (France)

2016-07-11

We report a crucial step towards single-object cavity electrodynamics in the mid-infrared spectral range using resonators that borrow functionalities from antennas. Room-temperature strong light-matter coupling is demonstrated in the mid-infrared between an intersubband transition and an extremely reduced number of sub-wavelength resonators. By exploiting 3D plasmonic nano-antennas featuring an out-of-plane geometry, we observed strong light-matter coupling in a very low number of resonators: only 16, more than 100 times better than what reported to date in this spectral range. The modal volume addressed by each nano-antenna is sub-wavelength-sized and it encompasses only ≈4400 electrons.

Orientation sensors by defocused imaging of single gold nano-bipyramids

Science.gov (United States)

Zhang, Fanwei; Li, Qiang; Rao, Wenye; Hu, Hongjin; Gao, Ye; Wu, Lijun

2018-01-01

Optical probes for nanoscale orientation sensing have attracted much attention in the field of single-molecule detections. Noble metal especially Au nanoparticles (NPs) exhibit extraordinary plasmonic properties, great photostability, excellent biocompatibility and nontoxicity, and thereby could be alternative labels to conventional applied organic dyes or quantum dots. One type of the most interesting metallic NPs is Au nanorods (AuNRs). Its anisotropic emission accompanied with anisotropic shape is potentially applicable in orientation sensing. Recently, we resolved the 3D orientation of single AuNRs within one frame by deliberately introducing an aberration (slight shift of the dipole away from the focal plane) to the imaging system1 . This defocused imaging technique is based on the electron transition dipole approximation and the fact that the dipole radiation exhibits an angular anisotropy. Since the photoluminescence quantum yield (PLQY) can be enhanced by the "lightning rod effect" (at a sharp angled surface) and localized SPR modes, that of the single Au nano-bipyramid (AuNB) with more sharp tips or edges was found to be doubled comparing to AuNRs with a same effective size2. Here, with a 532 nm excitation, we find that the PL properties of individual AuNBs can be described by three perpendicularly-arranged dipoles (with different ratios). Their PL defocused images are bright, clear and exhibit obvious anisotropy. These properties suggest that AuNBs are excellent candidates for orientation sensing labels in single molecule detections.

Label-free tracking of single extracellular vesicles in a nano-fluidic optical fiber (Conference Presentation)

Science.gov (United States)

van der Pol, Edwin; Weidlich, Stefan; Lahini, Yoav; Coumans, Frank A. W.; Sturk, Auguste; Nieuwland, Rienk; Schmidt, Markus A.; Faez, Sanli; van Leeuwen, Ton G.

2016-03-01

Background: Extracellular vesicles, such as exosomes, are abundantly present in human body fluids. Since the size, concentration and composition of these vesicles change during disease, vesicles have promising clinical applications, including cancer diagnosis. However, since ~70% of the vesicles have a diameter <70 nm, detection of single vesicles remains challenging. Thus far, vesicles <70 nm have only be studied by techniques that require the vesicles to be adhered to a surface. Consequently, the majority of vesicles have never been studied in their physiological environment. We present a novel label-free optical technique to track single vesicles <70 nm in suspension. Method: Urinary vesicles were contained within a single-mode light-guiding silica fiber containing a 600 nm nano-fluidic channel. Light from a diode laser (660 nm wavelength) was coupled to the fiber, resulting in a strongly confined optical mode in the nano-fluidic channel, which continuously illuminated the freely diffusing vesicles inside the channel. The elastic light scattering from the vesicles, in the direction orthogonal to the fiber axis, was collected using a microscope objective (NA=0.95) and imaged with a home-built microscope. Results: We have tracked single urinary vesicles as small as 35 nm by elastic light scattering. Please note that vesicles are low-refractive index (n<1.4) particles, which we confirmed by combining data on thermal diffusion and light scattering cross section. Conclusions: For the first time, we have studied vesicles <70 nm freely diffusing in suspension. The ease-of-use and performance of this technique support its potential for vesicle-based clinical applications.

Development of point Kernel radiation shielding analysis computer program implementing recent nuclear data and graphic user interfaces

International Nuclear Information System (INIS)

Kang, S.; Lee, S.; Chung, C.

2002-01-01

There is an increasing demand for safe and efficient use of radiation and radioactive work activity along with shielding analysis as a result the number of nuclear and conventional facilities using radiation or radioisotope rises. Most Korean industries and research institutes including Korea Power Engineering Company (KOPEC) have been using foreign computer programs for radiation shielding analysis. Korean nuclear regulations have introduced new laws regarding the dose limits and radiological guides as prescribed in the ICRP 60. Thus, the radiation facilities should be designed and operated to comply with these new regulations. In addition, the previous point kernel shielding computer code utilizes antiquated nuclear data (mass attenuation coefficient, buildup factor, etc) which were developed in 1950∼1960. Subsequently, the various nuclear data such mass attenuation coefficient, buildup factor, etc. have been updated during the past few decades. KOPEC's strategic directive is to become a self-sufficient and independent nuclear design technology company, thus KOPEC decided to develop a new radiation shielding computer program that included the latest regulatory requirements and updated nuclear data. This new code was designed by KOPEC with developmental cooperation with Hanyang University, Department of Nuclear Engineering. VisualShield is designed with a graphical user interface to allow even users unfamiliar to radiation shielding theory to proficiently prepare input data sets and analyzing output results

The Degradation of Mechanical Properties in Halloysite Nano clay-Polyester Nano composites Exposed in Seawater Environment

International Nuclear Information System (INIS)

Saharudin, M.S.; Saharudin, M. Sh.; Wei, J.; Shyha, I.; Inam, F.

2016-01-01

Polyester based polymers are extensively used in aggressive marine environments; however, inadequate data is available on the effects of the seawater on the polyester based nano composites mechanical properties. This paper reports the effect of seawater absorption on the mechanical properties degradation of halloysite nano clay-polyester nano composites. Results confirmed that the addition of halloysite nano clay into polyester matrix was found to increase seawater uptake and reduce mechanical properties compared to monolithic polyester. The maximum decreases in microhardness, tensile and flexural properties, and impact toughness were observed in case of 1 wt% nano clay. The microhardness decreased from 107 HV to 41.7 HV (61% decrease). Young s modulus decreased from 0.6 GPa to 0.4 GPa (33% decrease). The flexural modulus decreased from 0.6 GPa to 0.34 GPa (43% decrease). The impact toughness dropped from 0.71 kJ/m"2 to 0.48 kJ/m"2 (32% decrease). Interestingly, the fracture toughnessκ_1C increased with the addition of halloysite nano clay due to the plasticization effect of the resin matrix. SEM images revealed the significant reduction in mechanical properties in case of 1 wt% reinforcement which is attributed to the degradation of the nano clay-matrix interface influenced by seawater absorption and agglomeration of halloysite nano clay.

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....

Controlled deposition of functionalized silica coated zinc oxide nano-assemblies at the air/water interface for blood cancer detection

Energy Technology Data Exchange (ETDEWEB)

Pandey, Chandra Mouli [Biomedical Instrumentation Section, CSIR-National Physical Laboratory, New Delhi 110012 (India); Nanobioelectronics Laboratory, Department of Biotechnology, Delhi Technological University, Delhi 110042 (India); Dewan, Srishti [Biomedical Instrumentation Section, CSIR-National Physical Laboratory, New Delhi 110012 (India); Biomedical Engineering Department, Deenbandhu Chhotu Ram University of Science & Technology, Haryana 131039 (India); Chawla, Seema [Biomedical Engineering Department, Deenbandhu Chhotu Ram University of Science & Technology, Haryana 131039 (India); Yadav, Birendra Kumar [Rajiv Gandhi Cancer Institute and Research Centre, Rohini, Delhi 110085 (India); Sumana, Gajjala, E-mail: sumanagajjala@gmail.com [Biomedical Instrumentation Section, CSIR-National Physical Laboratory, New Delhi 110012 (India); Malhotra, Bansi Dhar, E-mail: bansi.malhotra@gmail.com [Biomedical Instrumentation Section, CSIR-National Physical Laboratory, New Delhi 110012 (India); Nanobioelectronics Laboratory, Department of Biotechnology, Delhi Technological University, Delhi 110042 (India)

2016-09-21

We report results of the studies relating to controlled deposition of the amino-functionalized silica-coated zinc oxide (Am-Si@ZnO) nano-assemblies onto an indium tin oxide (ITO) coated glass substrate using Langmuir-Blodgett (LB) technique. The monolayers have been deposited by transferring the spread solution of Am-Si@ZnO stearic acid prepared in chloroform at the air-water interface, at optimized pressure (16 mN/m), concentration (10 mg/ml) and temperature (23 °C). The high-resolution transmission electron microscopic studies of the Am-Si@ZnO nanocomposite reveal that the nanoparticles have a microscopic structure comprising of hexagonal assemblies of ZnO with typical dimensions of 30 nm. The surface morphology of the LB multilayer observed by scanning electron microscopy shows uniform surface of the Am-Si@ZnO film in the nanometer range (<80 nm). These electrodes have been utilized for chronic myelogenous leukemia (CML) detection by covalently immobilizing the amino-terminated oligonucleotide probe sequence via glutaraldehyde as a crosslinker. The response studies of these fabricated electrodes carried out using electrochemical impedance spectroscopy show that this Am-Si@ZnO LB film based nucleic acid sensor exhibits a linear response to complementary DNA (10{sup −6}–10{sup −16} M) with a detection limit of 1 × 10{sup −16} M. This fabricated platform is validated with clinical samples of CML positive patients and the results demonstrate its immense potential for clinical diagnosis. - Graphical abstract: Controlled deposition of functionalized silica coated zinc oxide nano-assemblies at the air/water interface for label free electrochemical detection of chronic myelogenous leukemia. - Highlights: • Stable and controlled deposition of Am-Si@ZnO nano-assemblies using LB technique. • Uniform monolayer deposition of the Am-Si@ZnO LB film within the nanometer range. • Am-Si@ZnO LB film shows enhanced electrochemical properties. • Fabricated

Tip-Enhanced Nano-Spectroscopy, Imaging, and Control: From Single Molecules to van der Waals Materials

Science.gov (United States)

Park, Kyoung-Duck

Photon-induced phenomena in molecules and other materials play a significant role in device applications as well as understanding their physical properties. While a range of device applications using organic and inorganic molecules and soft and hard materials have led striking developments in modern technologies, using bulk systems has reached the limit in their functions, performance, and regarding application range. Recently, low-dimensional systems have emerged as appealing resources for the advanced technologies based on their significantly improved functions and properties. Hence, understanding light-matter interactions at their natural length scale is of fundamental significance, in addition to the next generation device applications. This thesis demonstrates a range of new functions and behaviors of low-dimensional materials revealed and controlled by the advanced tip-enhanced near-field spectroscopy and imaging techniques exceeding the current instrumental limits. To understand the behaviors of zero-dimensional (0D) molecular systems in interacting environments, we explore new regimes in tip-enhanced Raman spectroscopy (TERS) and scanning near-field optical microscopy (SNOM), revealing the fundamental nature of single-molecule dynamics and nanoscale spatial heterogeneity of biomolecules on the cell membranes. To gain insight into intramolecular properties and dynamic processes of single molecules, we use TERS at cryogenic temperatures. From temperature-dependent line narrowing and splitting, we investigate and quantify ultrafast vibrational dephasing, intramolecular coupling, and conformational heterogeneity. Through correlation analysis of fluctuations of individual modes, we observe rotational motion and spectral fluctuations of single-molecule. We extend single-molecule spectroscopy study into in situ nano-biomolecular imaging of cancer cells by developing in-liquid SNOM. We use a new mechanical resonance control, achieving a high-Q force sensing of the

Automated voxelization of 3D atom probe data through kernel density estimation

International Nuclear Information System (INIS)

Srinivasan, Srikant; Kaluskar, Kaustubh; Dumpala, Santoshrupa; Broderick, Scott; Rajan, Krishna

2015-01-01

Identifying nanoscale chemical features from atom probe tomography (APT) data routinely involves adjustment of voxel size as an input parameter, through visual supervision, making the final outcome user dependent, reliant on heuristic knowledge and potentially prone to error. This work utilizes Kernel density estimators to select an optimal voxel size in an unsupervised manner to perform feature selection, in particular targeting resolution of interfacial features and chemistries. The capability of this approach is demonstrated through analysis of the γ / γ’ interface in a Ni–Al–Cr superalloy. - Highlights: • Develop approach for standardizing aspects of atom probe reconstruction. • Use Kernel density estimators to select optimal voxel sizes in an unsupervised manner. • Perform interfacial analysis of Ni–Al–Cr superalloy, using new automated approach. • Optimize voxel size to preserve the feature of interest and minimizing loss / noise.

Fluctuation in Interface and Electronic Structure of Single-Molecule Junctions Investigated by Current versus Bias Voltage Characteristics.

Science.gov (United States)

Isshiki, Yuji; Fujii, Shintaro; Nishino, Tomoaki; Kiguchi, Manabu

2018-03-14

Structural and electronic detail at the metal-molecule interface has a significant impact on the charge transport across the molecular junctions, but its precise understanding and control still remain elusive. On the single-molecule scale, the metal-molecule interface structures and relevant charge transport properties are subject to fluctuation, which contain the fundamental science of single-molecule transport and implication for manipulability of the transport properties in electronic devices. Here, we present a comprehensive approach to investigate the fluctuation in the metal-molecule interface in single-molecule junctions, based on current-voltage ( I- V) measurements in combination with first-principles simulation. Contrary to conventional molecular conductance studies, this I- V approach provides a correlated statistical description of both the degree of electronic coupling across the metal-molecule interface and the molecular orbital energy level. This statistical approach was employed to study fluctuation in single-molecule junctions of 1,4-butanediamine (DAB), pyrazine (PY), 4,4'-bipyridine (BPY), and fullerene (C 60 ). We demonstrate that molecular-dependent fluctuation of σ-, π-, and π-plane-type interfaces can be captured by analyzing the molecular orbital (MO) energy level under mechanical perturbation. While the MO level of DAB with the σ-type interface shows weak distance dependence and fluctuation, the MO level of PY, BPY, and C 60 features unique distance dependence and molecular-dependent fluctuation against the mechanical perturbation. The MO level of PY and BPY with the σ+π-type interface increases with the increase in the stretch distance. In contrast, the MO level of C 60 with the π-plane-type interface decreases with the increase in the stretching perturbation. This study provides an approach to resolve the structural and electronic fluctuation in the single-molecule junctions and insight into the molecular-dependent fluctuation in

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...

Ultrafast convolution/superposition using tabulated and exponential kernels on GPU

Energy Technology Data Exchange (ETDEWEB)

Chen Quan; Chen Mingli; Lu Weiguo [TomoTherapy Inc., 1240 Deming Way, Madison, Wisconsin 53717 (United States)

2011-03-15

Purpose: Collapsed-cone convolution/superposition (CCCS) dose calculation is the workhorse for IMRT dose calculation. The authors present a novel algorithm for computing CCCS dose on the modern graphic processing unit (GPU). Methods: The GPU algorithm includes a novel TERMA calculation that has no write-conflicts and has linear computation complexity. The CCCS algorithm uses either tabulated or exponential cumulative-cumulative kernels (CCKs) as reported in literature. The authors have demonstrated that the use of exponential kernels can reduce the computation complexity by order of a dimension and achieve excellent accuracy. Special attentions are paid to the unique architecture of GPU, especially the memory accessing pattern, which increases performance by more than tenfold. Results: As a result, the tabulated kernel implementation in GPU is two to three times faster than other GPU implementations reported in literature. The implementation of CCCS showed significant speedup on GPU over single core CPU. On tabulated CCK, speedups as high as 70 are observed; on exponential CCK, speedups as high as 90 are observed. Conclusions: Overall, the GPU algorithm using exponential CCK is 1000-3000 times faster over a highly optimized single-threaded CPU implementation using tabulated CCK, while the dose differences are within 0.5% and 0.5 mm. This ultrafast CCCS algorithm will allow many time-sensitive applications to use accurate dose calculation.

Role of interfaces i nthe design of ultra-high strength, radiation damage tolerant nanocomposites

Energy Technology Data Exchange (ETDEWEB)

Misra, Amit [Los Alamos National Laboratory; Wang, Yongqiang [Los Alamos National Laboratory; Nastasi, Michael A [Los Alamos National Laboratory; Baldwin, Jon K [Los Alamos National Laboratory; Wei, Qiangmin [Los Alamos National Laboratory; Li, Nan [Los Alamos National Laboratory; Mara, Nathan [Los Alamos National Laboratory; Zhang, Xinghang [Los Alamos National Laboratory; Fu, Engang [Los Alamos National Laboratory; Anderoglu, Osman [Los Alamos National Laboratory; Li, Hongqi [Los Alamos National Laboratory; Bhattacharyya, Dhriti [NON LANL

2010-12-09

The combination of high strength and high radiation damage tolerance in nanolaminate composites can be achieved when the individual layers in these composites are only a few nanometers thick and contain special interfaces that act both as obstacles to slip, as well as sinks for radiation-induced defects. The morphological and phase stabilities and strength and ductility of these nano-composites under ion irradiation are explored as a function of layer thickness, temperature and interface structure. Magnetron sputtered metallic multilayers such as Cu-Nb and V-Ag with a range of individual layer thickness from approximately 2 nm to 50 nm and the corresponding 1000 nm thick single layer films were implanted with helium ions at room temperature. Cross-sectional Transmission Electron Microscopy (TEM) was used to measure the distribution of helium bubbles and correlated with the helium concentration profile measured vis ion beam analysis techniques to obtain the helium concentration at which bubbles are detected in TEM. It was found that in multilayers the minimum helium concentration to form bubbles (approximately I nm in size) that are easily resolved in through-focus TEM imaging was several atomic %, orders of magnitude higher than that in single layer metal films. This observation is consistent with an increased solubility of helium at interfaces that is predicted by atomistic modeling of the atomic structures of fcc-bcc interfaces. At helium concentrations as high as 7 at.%, a uniform distribution of I nm diameter bubbles results in negligible irradiation hardening and loss of deformability in multi layers with layer thicknesses of a few nanometers. The control of atomic structures of interfaces to produce high helium solubility at interfaces is crucial in the design of nano-composite materials that are radiation damage tolerant. Reduced radiation damage also leads to a reduction in the irradiation hardening, particularly at layer thickness of approximately 5 run

Comparison of flux motion in type-II superconductors including pinning centers with the shapes of nano-rods and nano-particles by using 3D-TDGL simulation

International Nuclear Information System (INIS)

Ito, Shintaro; Ichino, Yusuke; Yoshida, Yutaka

2015-01-01

Highlights: • We constructed the 3D-TDGL simulator to calculate the flux motion. • We assumed two superconductors including only nano-rods and only nano-particles. • We succeeded to simulate the flux motion for various magnetic field angles. • If anyone introduce nano-rod, controlling the “single-kink” motion is very important. • The introduction of nano-particles is effective to pin the “single-kink” motion. - Abstract: Time-dependent Ginzburg–Landau (TDGL) equations are very useful method for simulation of the motion of flux quanta in type-II superconductors. We constructed the 3D-TDGL simulator and succeeded to simulate the motion of flux quanta in 3-dimension. We carried out the 3D-TDGL simulation to compare two superconductors which included only pinning centers with the shape of nano-rods and only nano-particle-like pinning centers in the viewpoint of the flux motion. As a result, a motion of “single-kink” caused the whole motion of a flux quantum in the superconductor including only the nano-rods. On the other hand, in the superconductor including the nano-particles, the flux quanta were pinned by the nano-particles in the various magnetic field applied angles. As the result, no “single-kink” occurred in the superconductor including the nano-particles. Therefore, the nano-particle-like pinning centers are effective shape to trap flux quanta for various magnetic field applied angles.

Optimizing Multiple Kernel Learning for the Classification of UAV Data

Directory of Open Access Journals (Sweden)

Caroline M. Gevaert

2016-12-01

Full Text Available Unmanned Aerial Vehicles (UAVs are capable of providing high-quality orthoimagery and 3D information in the form of point clouds at a relatively low cost. Their increasing popularity stresses the necessity of understanding which algorithms are especially suited for processing the data obtained from UAVs. The features that are extracted from the point cloud and imagery have different statistical characteristics and can be considered as heterogeneous, which motivates the use of Multiple Kernel Learning (MKL for classification problems. In this paper, we illustrate the utility of applying MKL for the classification of heterogeneous features obtained from UAV data through a case study of an informal settlement in Kigali, Rwanda. Results indicate that MKL can achieve a classification accuracy of 90.6%, a 5.2% increase over a standard single-kernel Support Vector Machine (SVM. A comparison of seven MKL methods indicates that linearly-weighted kernel combinations based on simple heuristics are competitive with respect to computationally-complex, non-linear kernel combination methods. We further underline the importance of utilizing appropriate feature grouping strategies for MKL, which has not been directly addressed in the literature, and we propose a novel, automated feature grouping method that achieves a high classification accuracy for various MKL methods.

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

SU-F-SPS-09: Parallel MC Kernel Calculations for VMAT Plan Improvement

International Nuclear Information System (INIS)

Chamberlain, S; French, S; Nazareth, D

2016-01-01

Purpose: Adding kernels (small perturbations in leaf positions) to the existing apertures of VMAT control points may improve plan quality. We investigate the calculation of kernel doses using a parallelized Monte Carlo (MC) method. Methods: A clinical prostate VMAT DICOM plan was exported from Eclipse. An arbitrary control point and leaf were chosen, and a modified MLC file was created, corresponding to the leaf position offset by 0.5cm. The additional dose produced by this 0.5 cm × 0.5 cm kernel was calculated using the DOSXYZnrc component module of BEAMnrc. A range of particle history counts were run (varying from 3 × 10"6 to 3 × 10"7); each job was split among 1, 10, or 100 parallel processes. A particle count of 3 × 10"6 was established as the lower range because it provided the minimal accuracy level. Results: As expected, an increase in particle counts linearly increases run time. For the lowest particle count, the time varied from 30 hours for the single-processor run, to 0.30 hours for the 100-processor run. Conclusion: Parallel processing of MC calculations in the EGS framework significantly decreases time necessary for each kernel dose calculation. Particle counts lower than 1 × 10"6 have too large of an error to output accurate dose for a Monte Carlo kernel calculation. Future work will investigate increasing the number of parallel processes and optimizing run times for multiple kernel calculations.

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...

MER SPICE Interface

Science.gov (United States)

Sayfi, Elias

2004-01-01

MER SPICE Interface is a software module for use in conjunction with the Mars Exploration Rover (MER) mission and the SPICE software system of the Navigation and Ancillary Information Facility (NAIF) at NASA's Jet Propulsion Laboratory. (SPICE is used to acquire, record, and disseminate engineering, navigational, and other ancillary data describing circumstances under which data were acquired by spaceborne scientific instruments.) Given a Spacecraft Clock value, MER SPICE Interface extracts MER-specific data from SPICE kernels (essentially, raw data files) and calculates values for Planet Day Number, Local Solar Longitude, Local Solar Elevation, Local Solar Azimuth, and Local Solar Time (UTC). MER SPICE Interface was adapted from a subroutine, denoted m98SpiceIF written by Payam Zamani, that was intended to calculate SPICE values for the Mars Polar Lander. The main difference between MER SPICE Interface and m98SpiceIf is that MER SPICE Interface does not explicitly call CHRONOS, a time-conversion program that is part of a library of utility subprograms within SPICE. Instead, MER SPICE Interface mimics some portions of the CHRONOS code, the advantage being that it executes much faster and can efficiently be called from a pipeline of events in a parallel processing environment.

Nano-modification to improve the ductility of cementitious composites

International Nuclear Information System (INIS)

Yeşilmen, Seda; Al-Najjar, Yazin; Balav, Mohammad Hatam; Şahmaran, Mustafa; Yıldırım, Gürkan; Lachemi, Mohamed

2015-01-01

Effect of nano-sized mineral additions on ductility of engineered cementitious composites (ECC) containing high volumes of fly ash was investigated at different hydration degrees. Various properties of ECC mixtures with different mineral additions were compared in terms of microstructural properties of matrix, fiber-matrix interface, and fiber surface to assess improvements in ductility. Microstructural characterization was made by measuring pore size distributions through mercury intrusion porosimetry (MIP). Hydration characteristics were assessed using thermogravimetric analysis/differential thermal analysis (TGA/DTA), and fiber-matrix interface and fiber surface characteristics were assessed using scanning electron microscopy (SEM) through a period of 90 days. Moreover, compressive and flexural strength developments were monitored for the same period. Test results confirmed that mineral additions could significantly improve both flexural strength and ductility of ECC, especially at early ages. Cheaper Nano-CaCO 3 was more effective compared to nano-silica. However, the crystal structure of CaCO 3 played a very important role in the range of expected improvements

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....

Pareto-path multitask multiple kernel learning.

Science.gov (United States)

Li, Cong; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

2015-01-01

A traditional and intuitively appealing Multitask Multiple Kernel Learning (MT-MKL) method is to optimize the sum (thus, the average) of objective functions with (partially) shared kernel function, which allows information sharing among the tasks. We point out that the obtained solution corresponds to a single point on the Pareto Front (PF) of a multiobjective optimization problem, which considers the concurrent optimization of all task objectives involved in the Multitask Learning (MTL) problem. Motivated by this last observation and arguing that the former approach is heuristic, we propose a novel support vector machine MT-MKL framework that considers an implicitly defined set of conic combinations of task objectives. We show that solving our framework produces solutions along a path on the aforementioned PF and that it subsumes the optimization of the average of objective functions as a special case. Using the algorithms we derived, we demonstrate through a series of experimental results that the framework is capable of achieving a better classification performance, when compared with other similar MTL approaches.

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...

The nano-micro interface bridging the micro and nano worlds

CERN Document Server

Werner, Matthias; Fecht, Hans-Jörg

2015-01-01

This second, enlarged edition has been fully updated to address the rapid progress made within this field in recent years. Internationally recognized experts provide comprehensive, first-hand information, resulting in an overview of the entire nano-micro world. In so doing, they cover aspects of funding and commercialization, the manufacture and future applications of nanomaterials, the fundamentals of nanostructures leading to macroscale objects as well as the ongoing miniaturization toward the nanoscale domain. Along the way, the authors explain the effects occurring at the nanoscale and the nanotechnological characterization techniques. An additional topic on the role of nanotechnology in energy and mobility covers the challenge of developing materials and devices, such as electrodes and membrane materials for fuel cells and catalysts for sustainable transportation. Also new to this edition are the latest figures for funding, investments, and commercialization prospects, as well as recent research programs...

Influence of cutting parameters on the depth of subsurface deformed layer in nano-cutting process of single crystal copper.

Science.gov (United States)

Wang, Quanlong; Bai, Qingshun; Chen, Jiaxuan; Su, Hao; Wang, Zhiguo; Xie, Wenkun

2015-12-01

Large-scale molecular dynamics simulation is performed to study the nano-cutting process of single crystal copper realized by single-point diamond cutting tool in this paper. The centro-symmetry parameter is adopted to characterize the subsurface deformed layers and the distribution and evolution of the subsurface defect structures. Three-dimensional visualization and measurement technology are used to measure the depth of the subsurface deformed layers. The influence of cutting speed, cutting depth, cutting direction, and crystallographic orientation on the depth of subsurface deformed layers is systematically investigated. The results show that a lot of defect structures are formed in the subsurface of workpiece during nano-cutting process, for instance, stair-rod dislocations, stacking fault tetrahedron, atomic clusters, vacancy defects, point defects. In the process of nano-cutting, the depth of subsurface deformed layers increases with the cutting distance at the beginning, then decreases at stable cutting process, and basically remains unchanged when the cutting distance reaches up to 24 nm. The depth of subsurface deformed layers decreases with the increase in cutting speed between 50 and 300 m/s. The depth of subsurface deformed layer increases with cutting depth, proportionally, and basically remains unchanged when the cutting depth reaches over 6 nm.

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.

Myndplay: Measuring Attention Regulation with Single Dry Electrode Brain Computer Interface

NARCIS (Netherlands)

van der Wal, C.N.; Irrmischer, M.; Guo, Y.; Friston, K.; Faisal, A.; Hill, S.; Peng, H.

2015-01-01

Future applications for the detection of attention can be helped by the development and validation of single electrode brain computer interfaces that are small and user-friendly. The two objectives of this study were: to (1) understand the correlates of attention regulation as detected with the

Finite size melting of spherical solid-liquid aluminium interfaces

DEFF Research Database (Denmark)

Chang, J.; Johnson, Erik; Sakai, T.

2009-01-01

We have investigated the melting of nano-sized cone shaped aluminium needles coated with amorphous carbon using transmission electron microscopy. The interface between solid and liquid aluminium was found to have spherical topology. For needles with fixed apex angle, the depressed melting tempera...... to the conclusion that the depressed melting temperature is not controlled solely by the inverse radius 1/R. Instead, we found a direct relation between the depressed melting temperature and the ratio between the solid-liquid interface area and the molten volume.......We have investigated the melting of nano-sized cone shaped aluminium needles coated with amorphous carbon using transmission electron microscopy. The interface between solid and liquid aluminium was found to have spherical topology. For needles with fixed apex angle, the depressed melting...

Option Valuation with Volatility Components, Fat Tails, and Nonlinear Pricing Kernels

DEFF Research Database (Denmark)

Babaoglu, Kadir Gokhan; Christoffersen, Peter; Heston, Steven

We nest multiple volatility components, fat tails and a U-shaped pricing kernel in a single option model and compare their contribution to describing returns and option data. All three features lead to statistically significant model improvements. A second volatility factor is economically most i...

Theoretical and experimental studies of single event effect induced by atmospheric muons on nano-metric technologies

International Nuclear Information System (INIS)

Li Cavoli, P.

2016-01-01

This study concerns the domain of the microelectronics. It consists in the study of the impact of the 3D morphology of the energy deposit on the Single Event Effect (SEE) modeling, induced by atmospheric muons. Over a first phase, the approach has consisted in the modeling of the energy deposit induced by protons in nano-metric volumes. For that purpose the use of the Monte Carlo code GEANT4 has allowed us to simulate and stock in a database the tracks characteristics of the energy deposit induced by protons. Once the approach validated for the protons, simulations of the energy deposit induced by muons have been realized. A CCD camera has been used in order to measure the radiative atmospheric environment and to constrain the modeling of the energy deposit induced by muons. This study highlights and quantify the contribution of the radial distribution of the energy deposit induced by protons in nano-metric volumes for the SEE prediction. On the other hand, the study shows that the contribution of the radial distribution of the energy deposit induced by muons in nano-metric volumes has a negligible impact on the SEE modeling. It will be interesting to realize measurements of the energy deposit induced by muons in nano-metric technologies under particle accelerator. This will allow to bring experimental data still nonexistent necessary to the development of new physical models more accurate on the modeling of the energy deposit induced by muons. (author)

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.

Nano-friction behavior of phosphorene.

Science.gov (United States)

Bai, Lichun; Liu, Bo; Srikanth, Narasimalu; Tian, Yu; Zhou, Kun

2017-09-01

Nano-friction of phosphorene plays a significant role in affecting the controllability and efficiency of applying strain engineering to tune its properties. So far, the friction behavior of phosphorene has not been studied. This work studies the friction of single-layer and bilayer phosphorene on an amorphous silicon substrate by sliding a rigid tip. For the single-layer phosphorene, it is found that its friction is highly anisotropic, i.e. the friction is larger along the armchair direction than that along the zigzag direction. Moreover, pre-strain of the phosphorene also exhibits anisotropic effects. The friction increases with the pre-strain along the zigzag direction, but decreases with that along the armchair direction. Furthermore, the strong adhesion between the phosphorene and its substrate increases the friction between the phosphorene and the tip. For bilayer phosphorene, its friction highly depends on its stacking mode, which determines the contact interface with a commensurate or incommensurate pattern. This friction behavior is quite unique and greatly differs from that of graphene and molybdenum disulfide. Detailed analysis reveals that this behavior results from the combination effect of the friction contact area, the potential-energy profile of phosphorene, and its unique elongation.

Self-assembled metal nano-multilayered film prepared by co-sputtering method

Science.gov (United States)

Xie, Tianle; Fu, Licai; Qin, Wen; Zhu, Jiajun; Yang, Wulin; Li, Deyi; Zhou, Lingping

2018-03-01

Nano-multilayered film is usually prepared by the arrangement deposition of different materials. In this paper, a self-assembled nano-multilayered film was deposited by simultaneous sputtering of Cu and W. The Cu/W nano-multilayered film was accumulated by W-rich layer and Cu-rich layer. Smooth interfaces with consecutive composition variation and semi-coherent even coherent relationship were identified, indicating that a spinodal-like structure with a modulation wavelength of about 20 nm formed during co-deposition process. The participation of diffusion barrier element, such as W, is believed the essential to obtain the nano-multilayered structure besides the technological parameters.

Flexible single-layer ionic organic-inorganic frameworks towards precise nano-size separation

Science.gov (United States)

Yue, Liang; Wang, Shan; Zhou, Ding; Zhang, Hao; Li, Bao; Wu, Lixin

2016-02-01

Consecutive two-dimensional frameworks comprised of molecular or cluster building blocks in large area represent ideal candidates for membranes sieving molecules and nano-objects, but challenges still remain in methodology and practical preparation. Here we exploit a new strategy to build soft single-layer ionic organic-inorganic frameworks via electrostatic interaction without preferential binding direction in water. Upon consideration of steric effect and additional interaction, polyanionic clusters as connection nodes and cationic pseudorotaxanes acting as bridging monomers connect with each other to form a single-layer ionic self-assembled framework with 1.4 nm layer thickness. Such soft supramolecular polymer frameworks possess uniform and adjustable ortho-tetragonal nanoporous structure in pore size of 3.4-4.1 nm and exhibit greatly convenient solution processability. The stable membranes maintaining uniform porous structure demonstrate precisely size-selective separation of semiconductor quantum dots within 0.1 nm of accuracy and may hold promise for practical applications in selective transport, molecular separation and dialysis systems.

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.

Reproducing kernel method with Taylor expansion for linear Volterra integro-differential equations

Directory of Open Access Journals (Sweden)

Azizallah Alvandi

2017-06-01

Full Text Available This research aims of the present a new and single algorithm for linear integro-differential equations (LIDE. To apply the reproducing Hilbert kernel method, there is made an equivalent transformation by using Taylor series for solving LIDEs. Shown in series form is the analytical solution in the reproducing kernel space and the approximate solution $ u_{N} $ is constructed by truncating the series to $ N $ terms. It is easy to prove the convergence of $ u_{N} $ to the analytical solution. The numerical solutions from the proposed method indicate that this approach can be implemented easily which shows attractive features.

An update on perfmon and the struggle to get into the Linux kernel

Energy Technology Data Exchange (ETDEWEB)

Nowak, Andrzej, E-mail: Andrzej.Nowak@cern.c [CERN openlab (Switzerland)

2010-04-01

At CHEP2007 we reported on the perfmon2 subsystem as a tool for interfacing to the PMUs (Performance Monitoring Units) which are found in the hardware of all modern processors (from AMD, Intel, SUN, IBM, MIPS, etc.). The intent was always to get the subsystem into the Linux kernel by default. This paper reports on how progress was made (after long discussions) and will also show the latest additions to the subsystems.

An update on perfmon and the struggle to get into the Linux kernel

International Nuclear Information System (INIS)

Nowak, Andrzej

2010-01-01

At CHEP2007 we reported on the perfmon2 subsystem as a tool for interfacing to the PMUs (Performance Monitoring Units) which are found in the hardware of all modern processors (from AMD, Intel, SUN, IBM, MIPS, etc.). The intent was always to get the subsystem into the Linux kernel by default. This paper reports on how progress was made (after long discussions) and will also show the latest additions to the subsystems.

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

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction.

Science.gov (United States)

Bandeira E Sousa, Massaine; Cuevas, Jaime; de Oliveira Couto, Evellyn Giselly; Pérez-Rodríguez, Paulino; Jarquín, Diego; Fritsche-Neto, Roberto; Burgueño, Juan; Crossa, Jose

2017-06-07

Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1) single-environment, main genotypic effect model (SM); (2) multi-environment, main genotypic effects model (MM); (3) multi-environment, single variance G×E deviation model (MDs); and (4) multi-environment, environment-specific variance G×E deviation model (MDe). Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB), and a nonlinear kernel Gaussian kernel (GK). The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets), having different numbers of maize hybrids evaluated in different environments for grain yield (GY), plant height (PH), and ear height (EH). Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK) had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied. Copyright © 2017 Bandeira e Sousa et al.

Genomic-Enabled Prediction in Maize Using Kernel Models with Genotype × Environment Interaction

Directory of Open Access Journals (Sweden)

Massaine Bandeira e Sousa

2017-06-01

Full Text Available Multi-environment trials are routinely conducted in plant breeding to select candidates for the next selection cycle. In this study, we compare the prediction accuracy of four developed genomic-enabled prediction models: (1 single-environment, main genotypic effect model (SM; (2 multi-environment, main genotypic effects model (MM; (3 multi-environment, single variance G×E deviation model (MDs; and (4 multi-environment, environment-specific variance G×E deviation model (MDe. Each of these four models were fitted using two kernel methods: a linear kernel Genomic Best Linear Unbiased Predictor, GBLUP (GB, and a nonlinear kernel Gaussian kernel (GK. The eight model-method combinations were applied to two extensive Brazilian maize data sets (HEL and USP data sets, having different numbers of maize hybrids evaluated in different environments for grain yield (GY, plant height (PH, and ear height (EH. Results show that the MDe and the MDs models fitted with the Gaussian kernel (MDe-GK, and MDs-GK had the highest prediction accuracy. For GY in the HEL data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 9 to 32%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 9 to 49%. For GY in the USP data set, the increase in prediction accuracy of SM-GK over SM-GB ranged from 0 to 7%. For the MM, MDs, and MDe models, the increase in prediction accuracy of GK over GB ranged from 34 to 70%. For traits PH and EH, gains in prediction accuracy of models with GK compared to models with GB were smaller than those achieved in GY. Also, these gains in prediction accuracy decreased when a more difficult prediction problem was studied.

A mechanically enhanced hybrid nano-stratified barrier with a defect suppression mechanism for highly reliable flexible OLEDs.

Science.gov (United States)

Jeong, Eun Gyo; Kwon, Seonil; Han, Jun Hee; Im, Hyeon-Gyun; Bae, Byeong-Soo; Choi, Kyung Cheol

2017-05-18

Understanding the mechanical behaviors of encapsulation barriers under bending stress is important when fabricating flexible organic light-emitting diodes (FOLEDs). The enhanced mechanical characteristics of a nano-stratified barrier were analyzed based on a defect suppression mechanism, and then experimentally demonstrated. Following the Griffith model, naturally-occurring cracks, which were caused by Zn etching at the interface of the nano-stratified structure, can curb the propagation of defects. Cross-section images after bending tests provided remarkable evidence to support the existence of a defect suppression mechanism. Many visible cracks were found in a single Al 2 O 3 layer, but not in the nano-stratified structure, due to the mechanism. The nano-stratified structure also enhanced the barrier's physical properties by changing the crystalline phase of ZnO. In addition, experimental results demonstrated the effect of the mechanism in various ways. The nano-stratified barrier maintained a low water vapor transmission rate after 1000 iterations of a 1 cm bending radius test. Using this mechanically enhanced hybrid nano-stratified barrier, FOLEDs were successfully encapsulated without losing mechanical or electrical performance. Finally, comparative lifetime measurements were conducted to determine reliability. After 2000 hours of constant current driving and 1000 iterations with a 1 cm bending radius, the FOLEDs retained 52.37% of their initial luminance, which is comparable to glass-lid encapsulation, with 55.96% retention. Herein, we report a mechanically enhanced encapsulation technology for FOLEDs using a nano-stratified structure with a defect suppression mechanism.

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

The eNanoMapper database for nanomaterial safety information.

Science.gov (United States)

Jeliazkova, Nina; Chomenidis, Charalampos; Doganis, Philip; Fadeel, Bengt; Grafström, Roland; Hardy, Barry; Hastings, Janna; Hegi, Markus; Jeliazkov, Vedrin; Kochev, Nikolay; Kohonen, Pekka; Munteanu, Cristian R; Sarimveis, Haralambos; Smeets, Bart; Sopasakis, Pantelis; Tsiliki, Georgia; Vorgrimmler, David; Willighagen, Egon

2015-01-01

The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs. The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms. We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the "representational state transfer" (REST) API enables building user friendly

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

Bio-inspired nano tools for neuroscience.

Science.gov (United States)

Das, Suradip; Carnicer-Lombarte, Alejandro; Fawcett, James W; Bora, Utpal

2016-07-01

Research and treatment in the nervous system is challenged by many physiological barriers posing a major hurdle for neurologists. The CNS is protected by a formidable blood brain barrier (BBB) which limits surgical, therapeutic and diagnostic interventions. The hostile environment created by reactive astrocytes in the CNS along with the limited regeneration capacity of the PNS makes functional recovery after tissue damage difficult and inefficient. Nanomaterials have the unique ability to interface with neural tissue in the nano-scale and are capable of influencing the function of a single neuron. The ability of nanoparticles to transcend the BBB through surface modifications has been exploited in various neuro-imaging techniques and for targeted drug delivery. The tunable topography of nanofibers provides accurate spatio-temporal guidance to regenerating axons. This review is an attempt to comprehend the progress in understanding the obstacles posed by the complex physiology of the nervous system and the innovations in design and fabrication of advanced nanomaterials drawing inspiration from natural phenomenon. We also discuss the development of nanomaterials for use in Neuro-diagnostics, Neuro-therapy and the fabrication of advanced nano-devices for use in opto-electronic and ultrasensitive electrophysiological applications. The energy efficient and parallel computing ability of the human brain has inspired the design of advanced nanotechnology based computational systems. However, extensive use of nanomaterials in neuroscience also raises serious toxicity issues as well as ethical concerns regarding nano implants in the brain. In conclusion we summarize these challenges and provide an insight into the huge potential of nanotechnology platforms in neuroscience. Copyright © 2016 Elsevier Ltd. All rights reserved.

a Comparison Study of Different Kernel Functions for Svm-Based Classification of Multi-Temporal Polarimetry SAR Data

Science.gov (United States)

Yekkehkhany, B.; Safari, A.; Homayouni, S.; Hasanlou, M.

2014-10-01

In this paper, a framework is developed based on Support Vector Machines (SVM) for crop classification using polarimetric features extracted from multi-temporal Synthetic Aperture Radar (SAR) imageries. The multi-temporal integration of data not only improves the overall retrieval accuracy but also provides more reliable estimates with respect to single-date data. Several kernel functions are employed and compared in this study for mapping the input space to higher Hilbert dimension space. These kernel functions include linear, polynomials and Radial Based Function (RBF). The method is applied to several UAVSAR L-band SAR images acquired over an agricultural area near Winnipeg, Manitoba, Canada. In this research, the temporal alpha features of H/A/α decomposition method are used in classification. The experimental tests show an SVM classifier with RBF kernel for three dates of data increases the Overall Accuracy (OA) to up to 3% in comparison to using linear kernel function, and up to 1% in comparison to a 3rd degree polynomial kernel function.

Comparison on exfoliated graphene nano-sheets and triturated graphite nano-particles for mode-locking the Erbium-doped fibre lasers

Science.gov (United States)

Yang, Chun-Yu; Lin, Yung-Hsiang; Wu, Chung-Lun; Cheng, Chih-Hsien; Tsai, Din-Ping; Lin, Gong-Ru

2018-06-01

Comparisons on exfoliated graphene nano-sheets and triturated graphite nano-particles for mode-locking the Erbium-doped fiber lasers (EDFLs) are performed. As opposed to the graphite nano-particles obtained by physically triturating the graphite foil, the tri-layer graphene nano-sheets is obtained by electrochemically exfoliating the graphite foil. To precisely control the size dispersion and the layer number of the exfoliated graphene nano-sheet, both the bias of electrochemical exfoliation and the speed of centrifugation are optimized. Under a threshold exfoliation bias of 3 volts and a centrifugation at 1000 rpm, graphene nano-sheets with an average diameter of 100  ±  40 nm can be obtained. The graphene nano-sheets with an area density of 15 #/µm2 are directly imprinted onto the end-face of a single-mode fiber made patchcord connector inside the EDFL cavity. Such electrochemically exfoliated graphene nano-sheets show comparable saturable absorption with standard single-graphene and perform the self-amplitude modulation better than physically triturated graphite nano-particles. The linear transmittance and modulation depth of the inserted graphene nano-sheets are 92.5% and 53%, respectively. Under the operation with a power gain of 21.5 dB, the EDFL can be passively mode-locked to deliver a pulsewidth of 454.5 fs with a spectral linewidth of 5.6 nm. The time-bandwidth product of 0.31 is close to the transform limit. The Kelly sideband frequency spacing of 1.34 THz is used to calculate the chirp coefficient as  ‑0.0015.

Plasticity analysis of nano-grain-sized NiAl alloy in an atomic scale

International Nuclear Information System (INIS)

Wang Jingyang; Wang Xiaowei; Rifkin, J.; Li Douxing

2001-12-01

The molecular dynamics method is used to simulate a uniaxial tensile deformation of 3.8nm nano-NiAl alloy with curved amorphous-like interfaces at 0K. Plastic deformation behaviour is studied by examining the strain-stress relationship and the microstructural evolution characteristic. Atomic level analysis showed that the micro-strain is essentially heterogeneous in simulated nano-phase samples. The plastic deformation is not only attributed to the plasticity of interfaces, but also accompanied with the plastic shear strain mechanism inside lattice distortion regions and grains. (author)

Electromagnetics of active coated nano-particles

DEFF Research Database (Denmark)

Arslanagic, Samel

2013-01-01

This work reviews the fundamental properties of several spherical and cylindrical active coated nano-particles excited by their respective single and/or multiple sources of radiation at optical frequencies. Particular attention is devoted to the influence of the source location and orientation, t......, the optical gain constant and the nano-particle material composition on the electric and magnetic near fields, the power flow density, the radiated power as well as the directivities. Resonant as well as quasi-transparent states will be emphasized in the discussion.......This work reviews the fundamental properties of several spherical and cylindrical active coated nano-particles excited by their respective single and/or multiple sources of radiation at optical frequencies. Particular attention is devoted to the influence of the source location and orientation...

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...

Tool wear of a single-crystal diamond tool in nano-groove machining of a quartz glass plate

International Nuclear Information System (INIS)

Yoshino, Masahiko; Nakajima, Satoshi; Terano, Motoki

2015-01-01

Tool wear characteristics of a diamond tool in ductile mode machining are presented in this paper. Nano-groove machining of a quartz glass plate was conducted to examine the tool wear rate of a single-crystal diamond tool. Effects of lubrication on the tool wear rate were also evaluated. A numerical simulation technique was developed to evaluate the tool temperature and normal stress acting on the wear surface. From the simulation results it was found that the tool temperature does not increase during the machining experiment. It is also demonstrated that tool wear is attributed to the abrasive wear mechanism, but the effect of the adhesion wear mechanism is minor in nano-groove machining. It is found that the tool wear rate is reduced by using water or kerosene as a lubricant. (paper)

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 ...

Silicon Nano wires with MoS_x and Pt as Electrocatalysts for Hydrogen Evolution Reaction

International Nuclear Information System (INIS)

Hsieh, S.H.; Ho, S.T.; Chen, W.J.

2016-01-01

A convenient method was used for synthesizing Pt-nanoparticle//silicon nano wires nano composites. Obtained Pt-/silicon nano wires electrocatalysts were characterized by transmission electron microscopy (TEM). The hydrogen evolution reaction efficiency of the Pt-/silicon nano wire nano composite catalysts was assessed by examining polarization and electrolysis measurements under solar light irradiations. The electrochemical characterizations demonstrate that Pt-/silicon nano wire electrodes exhibited an excellent catalytic activity for hydrogen evolution reaction in an acidic electrolyte. The hydrogen production capability of Pt-/silicon nano wires is also comparable to /silicon nano wires and Pt/silicon nano wires. Electrochemical impedance spectroscopy experiments suggest that the enhanced performance of Pt-/silicon nano wires can be attributed to the fast electron transfer between Pt-/silicon nano wire electrodes and electrolyte interfaces.

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....

Nano-and microstructure of air/oil/water interfaces

International Nuclear Information System (INIS)

McGillivray, D.; Mata, J.; White, J.; Zank, J.

2009-01-01

Full text: We report the creation of air/oil/water interfaces with variable thickness oil films, using polyisobutylen based (PIB) surfactants co-spread with long-chain paraffinic alkanes on clean water surfaces. The resultant stable oil layers are readily measurable with simple surface techniques, exhibit physical densities the same as expected for bulk oils, and are up to - 1 00 A thick above the water surface as determined using x-ray reflectometry. This provides a ready system for studying the competition of surfactants at the oil/water interface. Results from the competition of a non-ionic polyamide surfactant or an anionic sodium dodecyl sulfate with the PIB surfactant are reported. However, this smooth oil layer does not account for the total volume of spread oil, nor is the increase in thickness proportional to the film compression. Brewster angle microscopy (BAM) reveals surfactant and oil structures on the scale of 1 to 10μm at the interface. At low surface pressure (π m Nm-1) large, -10μm inhomogeneities are observed. Beyond a phase transition observed at ∼ 24 m Nm-1 a structure with a spongy appearance and a micron-scale texture develops. These structures have implications for understanding the microstructure at the oil/water interface in emulsions.

Nano-Reinforcement of Interfaces in Prepreg-Based Composites Using a Carbon Nanotubes Spraying Method

KAUST Repository

Almuhammadi, Khaled

2012-01-01

of epoxy resins used as matrix materials for CFRP composites can be increased by the addition of nano-sized fillers such as Carbon nanotubes (CNTs). CNTs are particularly well suited for this purpose because of their nano-scale diameter and high aspect

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.

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.)

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

Science.gov (United States)

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

Directory of Open Access Journals (Sweden)

Jaime Cuevas

2017-01-01

Full Text Available The phenomenon of genotype × environment (G × E interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects ( u that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP and Gaussian (Gaussian kernel, GK. The other model has the same genetic component as the first model ( u plus an extra component, f, that captures random effects between environments that were not captured by the random effects u . We used five CIMMYT data sets (one maize and four wheat that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u   and   f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u .

A review of nano-optics in metamaterial hybrid heterostructures

Energy Technology Data Exchange (ETDEWEB)

Singh, Mahi R. [Department of Physics and Astronomy, Western University, London N6G 3K7 (Canada)

2014-03-31

We present a review for the nonlinear nano-optics in quantum dots doped in a metamaterial heterostructure. The heterostructure is formed by depositing a metamaterial on a dielectric substrate and ensemble of noninteracting quantum dots are doped near the heterostructure interface. It is shown that there is enhancement of the second harmonic generation due to the surface plasmon polaritons field present at the interface.

Kernel learning at the first level of inference.

Science.gov (United States)

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

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

Global Polynomial Kernel Hazard Estimation

DEFF Research Database (Denmark)

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

2015-01-01

This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically redu...

Quantum tomography, phase-space observables and generalized Markov kernels

International Nuclear Information System (INIS)

Pellonpaeae, Juha-Pekka

2009-01-01

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

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

Science.gov (United States)

2013-01-01

Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

Fabrication and interfacing of nanochannel devices for single-molecule studies

International Nuclear Information System (INIS)

Hoang, H T; Berenschot, J W; De Boer, M J; Tas, N R; Haneveld, J; Elwenspoek, M C; Segers-Nolten, I M

2009-01-01

Nanochannel devices have been fabricated using standard micromachining techniques such as optical lithography, deposition and etching. 1D nanochannels with thin glass capping and through-wafer inlet/outlet ports were constructed. 2D nanochannels have been made transparent by oxidation of polysilicon channel wall for optical detection and these fragile channels were successfully connected to macro inlet ports. The interfacing from the macro world to the nanochannels was especially designed for optical observation of filling liquid inside nanochannels using an inverted microscope. Toward single-molecule studies, individual quantum dots were visualized in 150 nm height 1D nanochannels. The potential of 2D nanochannels for single-molecule studies was shown from a filling experiment with a fluorescent dye solution

Carbon Corrosion at Pt/C Interface in Proton Exchange Membrane Fuel Cell Environment

International Nuclear Information System (INIS)

Choi, Min Ho; Beam, Won Jin; Park, Chan Jin

2010-01-01

This study examined the carbon corrosion at Pt/C interface in proton exchange membrane fuel cell environment. The Pt nano particles were electrodeposited on carbon substrate, and then the corrosion behavior of the carbon electrode was examined. The carbon electrodes with Pt nano electrodeposits exhibited the higher oxidation rate and lower oxidation overpotential compared with that of the electrode without Pt. This phenomenon was more active at 75 .deg. C than 25 .deg. C. In addition, the current transients and the corresponding power spectral density (PSD) of the carbon electrodes with Pt nano electrodeposits were much higher than those of the electrode without Pt. The carbon corrosion at Pt/C interface was highly accelerated by Pt nano electrodeposits. Furthermore, the polarization and power density curves of PEMFC showed degradation in the performance due to a deterioration of cathode catalyst material and Pt dissolution

Some Observations on Carbon Nano tubes Susceptibility to Cell Phagocytosis

International Nuclear Information System (INIS)

Fraczek-Szczypta, A.; Menaszek, E.; Blazewicz, S.; Menaszek, E.

2011-01-01

The aim of this study was to assess the influence of different types of carbon nano tubes (CNTs) on cell phagocytosis. Three kinds of carbon nano tubes: single-walled carbon nano horns (SWCNHs), multi walled carbon nano tubes (MWCNTs), and ultra-long single-walled carbon nano tubes (ULSWCNTs) before and after additional chemical functionalization were seeded with macrophage cell culture. Prior to biological testing, the CNTs were subjected to dispersion process with the use of phosphate buffered solution (PBS) and PBS containing surfactant (Tween 20) or dimethyl sulfoxide (DMSO). The results indicate that the cells interaction with an individual nano tube is entirely different as compared to CNTs in the form of aggregate. The presence of the surfactant favors the CNTs dispersion in culture media and facilitates phagocytosis process, while it has disadvantageous influence on cells morphology. The cells phagocytosis is a more effective for MWCNTs and SWCNHs after their chemical functionalization. Moreover, these nano tubes were well dispersed in culture media without using DMSO or surfactant. The functionalized carbon nano tubes were easily dispersed in pure PBS and seeded with cells

Fabrication of three-dimensional MIS nano-capacitor based on nano-imprinted single crystal silicon nanowire arrays

KAUST Repository

Zhai, Yujia

2012-11-26

We report fabrication of single crystalline silicon nanowire based-three-dimensional MIS nano-capacitors for potential analog and mixed signal applications. The array of nanowires is patterned by Step and Flash Imprint Lithography (S-FIL). Deep silicon etching (DSE) is used to form the nanowires with high aspect ratio, increase the electrode area and thus significantly enhance the capacitance. High-! dielectric is deposited by highly conformal atomic layer deposition (ALD) Al2O3 over the Si nanowires, and sputtered metal TaN serves as the electrode. Electrical measurements of fabricated capacitors show the expected increase of capacitance with greater nanowire height and decreasing dielectric thickness, consistent with calculations. Leakage current and time-dependent dielectric breakdown (TDDB) are also measured and compared with planar MIS capacitors. In view of greater interest in 3D transistor architectures, such as FinFETs, 3D high density MIS capacitors offer an attractive device technology for analog and mixed signal applications. - See more at: http://www.eurekaselect.com/105099/article#sthash.EzeJxk6j.dpuf

Fabrication of three-dimensional MIS nano-capacitor based on nano-imprinted single crystal silicon nanowire arrays

KAUST Repository

Zhai, Yujia; Palard, Marylene; Mathew, Leo; Hussain, Muhammad Mustafa; Willson, Grant Grant; Tutuc, Emanuel; Banerjee, Sanjay Kumar

2012-01-01

We report fabrication of single crystalline silicon nanowire based-three-dimensional MIS nano-capacitors for potential analog and mixed signal applications. The array of nanowires is patterned by Step and Flash Imprint Lithography (S-FIL). Deep silicon etching (DSE) is used to form the nanowires with high aspect ratio, increase the electrode area and thus significantly enhance the capacitance. High-! dielectric is deposited by highly conformal atomic layer deposition (ALD) Al2O3 over the Si nanowires, and sputtered metal TaN serves as the electrode. Electrical measurements of fabricated capacitors show the expected increase of capacitance with greater nanowire height and decreasing dielectric thickness, consistent with calculations. Leakage current and time-dependent dielectric breakdown (TDDB) are also measured and compared with planar MIS capacitors. In view of greater interest in 3D transistor architectures, such as FinFETs, 3D high density MIS capacitors offer an attractive device technology for analog and mixed signal applications. - See more at: http://www.eurekaselect.com/105099/article#sthash.EzeJxk6j.dpuf

Relationship between attenuation coefficients and dose-spread kernels

International Nuclear Information System (INIS)

Boyer, A.L.

1988-01-01

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

Mixture Density Mercer Kernels: A Method to Learn Kernels

Data.gov (United States)

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

Integral equations with contrasting kernels

Directory of Open Access Journals (Sweden)

Theodore Burton

2008-01-01

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

Kernel methods in orthogonalization of multi- and hypervariate data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2009-01-01

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

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

Protein-material interactions: From micro-to-nano scale

International Nuclear Information System (INIS)

Tsapikouni, Theodora S.; Missirlis, Yannis F.

2008-01-01

The article presents a survey on the significance of protein-material interactions, the mechanisms which control them and the techniques used for their study. Protein-surface interactions play a key role in regenerative medicine, drug delivery, biosensor technology and chromatography, while it is related to various undesired effects such as biofouling and bio-prosthetic malfunction. Although the effects of protein-surface interaction concern the micro-scale, being sometimes obvious even with bare eyes, they derive from biophysical events at the nano-scale. The sequential steps for protein adsorption involve events at the single biomolecule level and the forces driving or inhibiting protein adsorption act at the molecular level too. Following the scaling of protein-surface interactions, various techniques have been developed for their study both in the micro- and nano-scale. Protein labelling with radioisotopes or fluorescent probes, colorimetric assays and the quartz crystal microbalance were the first techniques used to monitor protein adsorption isotherms, while the surface force apparatus was used to measure the interaction forces between protein layers at the micro-scale. Recently, more elaborate techniques like total internal reflection fluorescence (TIRF), Fourier transform infrared spectroscopy (FTIR), surface plasmon resonance, Raman spectroscopy, ellipsometry and time of flight secondary ion mass spectrometry (ToF-SIMS) have been applied for the investigation of protein density, structure or orientation at the interfaces. However, a turning point in the study of protein interactions with the surfaces was the invention and the wide-spread use of atomic force microscopy (AFM) which can both image single protein molecules on surfaces and directly measure the interaction force

Parsimonious Wavelet Kernel Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Wang Qin

2015-11-01

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

Difference between standard and quasi-conformal BFKL kernels

International Nuclear Information System (INIS)

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

2012-01-01

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

Kernel Tuning and Nonuniform Influence on Optical and Electrochemical Gaps of Bimetal Nanoclusters.

Science.gov (United States)

He, Lizhong; Yuan, Jinyun; Xia, Nan; Liao, Lingwen; Liu, Xu; Gan, Zibao; Wang, Chengming; Yang, Jinlong; Wu, Zhikun

2018-03-14

Fine tuning nanoparticles with atomic precision is exciting and challenging and is critical for tuning the properties, understanding the structure-property correlation and determining the practical applications of nanoparticles. Some ultrasmall thiolated metal nanoparticles (metal nanoclusters) have been shown to be precisely doped, and even the protecting staple metal atom could be precisely reduced. However, the precise addition or reduction of the kernel atom while the other metal atoms in the nanocluster remain the same has not been successful until now, to the best of our knowledge. Here, by carefully selecting the protecting ligand with adequate steric hindrance, we synthesized a novel nanocluster in which the kernel can be regarded as that formed by the addition of two silver atoms to both ends of the Pt@Ag 12 icosohedral kernel of the Ag 24 Pt(SR) 18 (SR: thiolate) nanocluster, as revealed by single crystal X-ray crystallography. Interestingly, compared with the previously reported Ag 24 Pt(SR) 18 nanocluster, the as-obtained novel bimetal nanocluster exhibits a similar absorption but a different electrochemical gap. One possible explanation for this result is that the kernel tuning does not essentially change the electronic structure, but obviously influences the charge on the Pt@Ag 12 kernel, as demonstrated by natural population analysis, thus possibly resulting in the large electrochemical gap difference between the two nanoclusters. This work not only provides a novel strategy to tune metal nanoclusters but also reveals that the kernel change does not necessarily alter the optical and electrochemical gaps in a uniform manner, which has important implications for the structure-property correlation of nanoparticles.

The eNanoMapper database for nanomaterial safety information

Directory of Open Access Journals (Sweden)

Nina Jeliazkova

2015-07-01

Full Text Available Background: The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs. Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs.Results: The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API, and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms.Conclusion: We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the “representational state

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...

Analysis about diamond tool wear in nano-metric cutting of single crystal silicon using molecular dynamics method

Science.gov (United States)

Wang, Zhiguo; Liang, Yingchun; Chen, Mingjun; Tong, Zhen; Chen, Jiaxuan

2010-10-01

Tool wear not only changes its geometry accuracy and integrity, but also decrease machining precision and surface integrity of workpiece that affect using performance and service life of workpiece in ultra-precision machining. Scholars made a lot of experimental researches and stimulant analyses, but there is a great difference on the wear mechanism, especially on the nano-scale wear mechanism. In this paper, the three-dimensional simulation model is built to simulate nano-metric cutting of a single crystal silicon with a non-rigid right-angle diamond tool with 0 rake angle and 0 clearance angle by the molecular dynamics (MD) simulation approach, which is used to investigate the diamond tool wear during the nano-metric cutting process. A Tersoff potential is employed for the interaction between carbon-carbon atoms, silicon-silicon atoms and carbon-silicon atoms. The tool gets the high alternating shear stress, the tool wear firstly presents at the cutting edge where intension is low. At the corner the tool is splitted along the {1 1 1} crystal plane, which forms the tipping. The wear at the flank face is the structure transformation of diamond that the diamond structure transforms into the sheet graphite structure. Owing to the tool wear the cutting force increases.

Identification of Fusarium damaged wheat kernels using image analysis

Directory of Open Access Journals (Sweden)

Ondřej Jirsa

2011-01-01

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

X-ray specular reflection and fluorescence study of nano-films

International Nuclear Information System (INIS)

Zheludeva, S.; Novikova, N.

2001-01-01

The techniques that combine the advantages of high-resolution structure sensitive x-ray methods with spectroscopic selectivity of data obtained are shown to be extremely promising for characterization of organic and inorganic nano films and nano structures. Fluorescence yield angular dependences exited by complicated evanescent wave / x-ray standing wave pattern at total reflection and glancing incidence can be used to detect structure position of different ions in organic systems and alien interfacial layers in inorganic multilayers;, to get information about interdiffusion at the interfaces of Langmuir- Blodgett (L-B) films and artificial inorganic - x-ray mirrors; to study ion permeation through L-B nano structures - models of biomembrans; to obtain nano - film thickness and density; to get precisely the parameters of small d-space multilayer mirrors, ets

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

Science.gov (United States)

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Progress in nano-electro optics characterization of nano-optical materials and optical near-field interactions

CERN Document Server

Ohtsu, Motoichi

2005-01-01

This volume focuses on the characterization of nano-optical materials and optical-near field interactions. It begins with the techniques for characterizing the magneto-optical Kerr effect and continues with methods to determine structural and optical properties in high-quality quantum wires with high spatial uniformity. Further topics include: near-field luminescence mapping in InGaN/GaN single quantum well structures in order to interpret the recombination mechanism in InGaN-based nano-structures; and theoretical treatment of the optical near field and optical near-field interactions, providing the basis for investigating the signal transport and associated dissipation in nano-optical devices. Taken as a whole, this overview will be a valuable resource for engineers and scientists working in the field of nano-electro-optics.

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

Science.gov (United States)

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

2015-05-01

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

Brownian motion of a nano-colloidal particle: the role of the solvent.

Science.gov (United States)

Torres-Carbajal, Alexis; Herrera-Velarde, Salvador; Castañeda-Priego, Ramón

2015-07-15

Brownian motion is a feature of colloidal particles immersed in a liquid-like environment. Usually, it can be described by means of the generalised Langevin equation (GLE) within the framework of the Mori theory. In principle, all quantities that appear in the GLE can be calculated from the molecular information of the whole system, i.e., colloids and solvent molecules. In this work, by means of extensive Molecular Dynamics simulations, we study the effects of the microscopic details and the thermodynamic state of the solvent on the movement of a single nano-colloid. In particular, we consider a two-dimensional model system in which the mass and size of the colloid are two and one orders of magnitude, respectively, larger than the ones associated with the solvent molecules. The latter ones interact via a Lennard-Jones-type potential to tune the nature of the solvent, i.e., it can be either repulsive or attractive. We choose the linear momentum of the Brownian particle as the observable of interest in order to fully describe the Brownian motion within the Mori framework. We particularly focus on the colloid diffusion at different solvent densities and two temperature regimes: high and low (near the critical point) temperatures. To reach our goal, we have rewritten the GLE as a second kind Volterra integral in order to compute the memory kernel in real space. With this kernel, we evaluate the momentum-fluctuating force correlation function, which is of particular relevance since it allows us to establish when the stationarity condition has been reached. Our findings show that even at high temperatures, the details of the attractive interaction potential among solvent molecules induce important changes in the colloid dynamics. Additionally, near the critical point, the dynamical scenario becomes more complex; all the correlation functions decay slowly in an extended time window, however, the memory kernel seems to be only a function of the solvent density. Thus, the

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.

IDENTIFICATION AND MAPPING OF A GENE FOR RICE SLENDER KERNEL USING Oryza glumaepatula INTROGRESSION LINES

Directory of Open Access Journals (Sweden)

Sobrizal Sobrizal

2016-10-01

Full Text Available World demand for superior rice grain quality tends to increase. One of the  criteria of appearance quality of rice grain is grain shape. Rice consumers  exhibit wide preferences for grain shape, but most Indonesian rice consumers prefer long and slender grain. The objectives of this study were to identify and map a gene for rice slender kernel trait using Oryza  glumaepatula introgression lines with O. sativa cv. Taichung 65 genetic background. A segregation analysis of BC4F2 population derived from backcrosses of a donor parent O. glumaepatula into a recurrent parent Taichung 65 showed that the slender kernel was controlled by a single recessive gene. This new identified gene was designated as sk1 (slender kernel 1. Moreover, based on the RFLP analyses using 14 RFLP markers located on chromosomes 2, 8, 9, and 10 in which the O. glumaepatula chromosomal segments were retained in BC4F2 population, the sk1 was located between RFLP markers C679 and C560 on the long arm of chromosome 2, with map distances of 2.8 and 1.5 cM, respectively. The wild rice O. glumaepatula carried a recessive allele for slender kernel. This allele may be useful in breeding of rice with slender kernel types. In addition, the development of plant materials and RFLP map associated with slender kernel in this study is the preliminary works in the effort to isolate this important grain shape gene.

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%.

Salus: Kernel Support for Secure Process Compartments

Directory of Open Access Journals (Sweden)

Raoul Strackx

2015-01-01

Full Text Available Consumer devices are increasingly being used to perform security and privacy critical tasks. The software used to perform these tasks is often vulnerable to attacks, due to bugs in the application itself or in included software libraries. Recent work proposes the isolation of security-sensitive parts of applications into protected modules, each of which can be accessed only through a predefined public interface. But most parts of an application can be considered security-sensitive at some level, and an attacker who is able to gain inapplication level access may be able to abuse services from protected modules. We propose Salus, a Linux kernel modification that provides a novel approach for partitioning processes into isolated compartments sharing the same address space. Salus significantly reduces the impact of insecure interfaces and vulnerable compartments by enabling compartments (1 to restrict the system calls they are allowed to perform, (2 to authenticate their callers and callees and (3 to enforce that they can only be accessed via unforgeable references. We describe the design of Salus, report on a prototype implementation and evaluate it in terms of security and performance. We show that Salus provides a significant security improvement with a low performance overhead, without relying on any non-standard hardware support.

Local impedance measurement of an electrode/single-pentacene-grain interface by frequency-modulation scanning impedance microscopy

Energy Technology Data Exchange (ETDEWEB)

Kimura, Tomoharu; Yamada, Hirofumi, E-mail: h-yamada@kuee.kyoto-u.ac.jp [Department of Electronic Science and Engineering, Kyoto University, Kyoto 615-8510 (Japan); Kobayashi, Kei [Department of Electronic Science and Engineering, Kyoto University, Kyoto 615-8510 (Japan); The Hakubi Center for Advanced Research, Kyoto University, Kyoto 615-8520 (Japan)

2015-08-07

The device performances of organic thin film transistors are often limited by the metal–organic interface because of the disordered molecular layers at the interface and the energy barriers against the carrier injection. It is important to study the local impedance at the interface without being affected by the interface morphology. We combined frequency modulation atomic force microscopy with scanning impedance microscopy (SIM) to sensitively measure the ac responses of the interface to an ac voltage applied across the interface and the dc potential drop at the interface. By using the frequency-modulation SIM (FM-SIM) technique, we characterized the interface impedance of a Pt electrode and a single pentacene grain as a parallel circuit of a contact resistance and a capacitance. We found that the reduction of the contact resistance was caused by the reduction of the energy level mismatch at the interface by the FM-SIM measurements, demonstrating the usefulness of the FM-SIM technique for investigation of the local interface impedance without being affected by its morphology.

Consistent Valuation across Curves Using Pricing Kernels

Directory of Open Access Journals (Sweden)

Andrea Macrina

2018-03-01

Full Text Available The general problem of asset pricing when the discount rate differs from the rate at which an asset’s cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each identified by a yield curve having its own market, credit and liquidity risk characteristics. The proposed framework precludes arbitrage within each market, while the definition of a curve-conversion factor process links all markets in a consistent arbitrage-free manner. A pricing formula is then derived, referred to as the across-curve pricing formula, which enables consistent valuation and hedging of financial instruments across curves (and markets. As a natural application, a consistent multi-curve framework is formulated for emerging and developed inter-bank swap markets, which highlights an important dual feature of the curve-conversion factor process. Given this multi-curve framework, existing multi-curve approaches based on HJM and rational pricing kernel models are recovered, reviewed and generalised and single-curve models extended. In another application, inflation-linked, currency-based and fixed-income hybrid securities are shown to be consistently valued using the across-curve valuation method.

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

SVM Classifier - a comprehensive java interface for support vector machine classification of microarray data.

Science.gov (United States)

Pirooznia, Mehdi; Deng, Youping

2006-12-12

Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1-BRCA2 samples with RBF kernel of SVM. We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at http://mfgn.usm.edu/ebl/svm/.

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...

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....

Spontaneous nano-gap formation in Ag film using NaCl sacrificial layer for Raman enhancement

Science.gov (United States)

Min, Kyungchan; Jeon, Wook Jin; Kim, Youngho; Choi, Jae-Young; Yu, Hak Ki

2018-03-01

We report the method of fabrication of nano-gaps (known as hot spots) in Ag thin film using a sodium chloride (NaCl) sacrificial layer for Raman enhancement. The Ag thin film (20-50 nm) on the NaCl sacrificial layer undergoes an interfacial reaction due to the AgCl formed at the interface during water molecule intercalation. The intercalated water molecules can dissolve the NaCl molecules at interfaces and form the ionic state of Na+ and Cl-, promoting the AgCl formation. The Ag atoms can migrate by the driving force of this interfacial reaction, resulting in the formation of nano-size gaps in the film. The surface-enhanced Raman scattering activity of Ag films with nano-size gaps has been investigated using Raman reporter molecules, Rhodamine 6G (R6G).

Enhanced gluten properties in soft kernel durum wheat

Science.gov (United States)

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

7 CFR 981.61 - Redetermination of kernel weight.

Science.gov (United States)

2010-01-01

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

Eucalyptus-Palm Kernel Oil Blends: A Complete Elimination of Diesel in a 4-Stroke VCR Diesel Engine

Directory of Open Access Journals (Sweden)

Srinivas Kommana

2015-01-01

Full Text Available Fuels derived from biomass are mostly preferred as alternative fuels for IC engines as they are abundantly available and renewable in nature. The objective of the study is to identify the parameters that influence gross indicated fuel conversion efficiency and how they are affected by the use of biodiesel relative to petroleum diesel. Important physicochemical properties of palm kernel oil and eucalyptus blend were experimentally evaluated and found within acceptable limits of relevant standards. As most of vegetable oils are edible, growing concern for trying nonedible and waste fats as alternative to petrodiesel has emerged. In present study diesel fuel is completely replaced by biofuels, namely, methyl ester of palm kernel oil and eucalyptus oil in various blends. Different blends of palm kernel oil and eucalyptus oil are prepared on volume basis and used as operating fuel in single cylinder 4-stroke variable compression ratio diesel engine. Performance and emission characteristics of these blends are studied by varying the compression ratio. In the present experiment methyl ester extracted from palm kernel oil is considered as ignition improver and eucalyptus oil is considered as the fuel. The blends taken are PKE05 (palm kernel oil 95 + eucalyptus 05, PKE10 (palm kernel oil 90 + eucalyptus 10, and PKE15 (palm kernel 85 + eucalyptus 15. The results obtained by operating with these fuels are compared with results of pure diesel; finally the most preferable combination and the preferred compression ratio are identified.

Nanoscale Affinity Chip Interface for Coupling Inhibition SPR Immunosensor Screening with Nano-LC TOF MS

NARCIS (Netherlands)

Marchesini, G.R.; Buijs, J.; Haasnoot, W.; Hooijerink, H.; Jansson, O.; Nielen, M.W.F.

2008-01-01

The on-line nanoscale coupling of a surface plasmon resonance (SPR)-based inhibition biosensor immunoassay (iBIA) for the screening of low molecular weight molecules with nano-liquid-chromatography electrospray ionization time-of-flight mass spectrometry (nano-LC ESI TOF MS) for identification is

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.

SNP typing on the NanoChip electronic microarray

DEFF Research Database (Denmark)

Børsting, Claus; Sanchez Sanchez, Juan Jose; Morling, Niels

2005-01-01

We describe a single nucleotide polymorphism (SNP) typing protocol developed for the NanoChip electronic microarray. The NanoChip array consists of 100 electrodes covered by a thin hydrogel layer containing streptavidin. An electric currency can be applied to one, several, or all electrodes...

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...

Nano-structural characteristics and optical properties of silver chiral nano-flower sculptured thin films

International Nuclear Information System (INIS)

Savaloni, Hadi; Haydari-Nasab, Fatemh; Malmir, Mariam

2011-01-01

Silver chiral nano-flowers with 3-, 4- and 5-fold symmetry were produced using oblique angle deposition method in conjunction with the rotation of sample holder with different speeds at different sectors of each revolution corresponding to symmetry order of the acquired nano-flower. Atomic force microscopy (AFM) and field emission scanning electron microscopy (FESEM), were employed to obtain morphology and nano-structure of the films. Optical characteristics of silver chiral nano-flower thin films were obtained using single beam spectrophotometer with both s- and p-polarization incident light at 30 o and 70 o incidence angles and at different azimuthal angles (φ). Optical spectra showed both TM (TDM (transverse dipole mode) and TQM (transverse quadruple mode)) and LM (longitudinal mode) Plasmon resonance peaks. For 3- and 4-fold symmetry chiral nano-flowers the s-polarization extinction spectra obtained at different azimuthal angles did not show significant change in the Plasmon peak position while 5-fold symmetry chiral nano-flower showed a completely different behavior, which may be the result of increased surface anisotropy, so when the φ angle is changed the s-polarization response from the surface can change more significantly than that for lower symmetries. In general, for 3-, 4- and 5-fold symmetry chiral nano-flowers a sharp peak at lower wavelengths ( o incidence angle.

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.

ADSORPTION OF COPPER FROM AQUEOUS SOLUTION BY ELAIS GUINEENSIS KERNEL ACTIVATED CARBON

Directory of Open Access Journals (Sweden)

NAJUA DELAILA TUMIN

2008-08-01

Full Text Available In this study, a series of batch laboratory experiments were conducted in order to investigate the feasibility of Elais Guineensis kernel or known as palm kernel shell (PKS-based activated carbon for the removal of copper from aqueous solution by the adsorption process. Investigation was carried out by studying the influence of initial solution pH, adsorbent dosage and initial concentration of copper. The particle size of PKS used was categorized as PKS–M. All batch experiments were carried out at a constant temperature of 30°C (±2°C using mechanical shaker that operated at 100 rpm. The single component equilibrium data was analyzed using Langmuir, Freundlich, Redlich-Peterson, Temkin and Toth adsorption isotherms.

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

QTL Mapping of Kernel Number-Related Traits and Validation of One Major QTL for Ear Length in Maize.

Science.gov (United States)

Huo, Dongao; Ning, Qiang; Shen, Xiaomeng; Liu, Lei; Zhang, Zuxin

2016-01-01

The kernel number is a grain yield component and an important maize breeding goal. Ear length, kernel number per row and ear row number are highly correlated with the kernel number per ear, which eventually determines the ear weight and grain yield. In this study, two sets of F2:3 families developed from two bi-parental crosses sharing one inbred line were used to identify quantitative trait loci (QTL) for four kernel number-related traits: ear length, kernel number per row, ear row number and ear weight. A total of 39 QTLs for the four traits were identified in the two populations. The phenotypic variance explained by a single QTL ranged from 0.4% to 29.5%. Additionally, 14 overlapping QTLs formed 5 QTL clusters on chromosomes 1, 4, 5, 7, and 10. Intriguingly, six QTLs for ear length and kernel number per row overlapped in a region on chromosome 1. This region was designated qEL1.10 and was validated as being simultaneously responsible for ear length, kernel number per row and ear weight in a near isogenic line-derived population, suggesting that qEL1.10 was a pleiotropic QTL with large effects. Furthermore, the performance of hybrids generated by crossing 6 elite inbred lines with two near isogenic lines at qEL1.10 showed the breeding value of qEL1.10 for the improvement of the kernel number and grain yield of maize hybrids. This study provides a basis for further fine mapping, molecular marker-aided breeding and functional studies of kernel number-related traits in maize.

Linear and kernel methods for multi- and hypervariate change detection

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Canty, Morton J.

2010-01-01

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

Kernel based orthogonalization for change detection in hyperspectral images

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

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

Mitigation of artifacts in rtm with migration kernel decomposition

KAUST Repository

Zhan, Ge; Schuster, Gerard T.

2012-01-01

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

Semi-Supervised Kernel PCA

DEFF Research Database (Denmark)

Walder, Christian; Henao, Ricardo; Mørup, Morten

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

Adaptive Metric Kernel Regression

DEFF Research Database (Denmark)

Goutte, Cyril; Larsen, Jan

1998-01-01

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

Nano Mechanical Machining Using AFM Probe

Science.gov (United States)

Mostofa, Md. Golam

and burr formations through intermittent cutting. Combining the AFM probe based machining with vibration-assisted machining enhanced nano mechanical machining processes by improving the accuracy, productivity and surface finishes. In this study, several scratching tests are performed with a single crystal diamond AFM probe to investigate the cutting characteristics and model the ploughing cutting forces. Calibration of the probe for lateral force measurements, which is essential, is also extended through the force balance method. Furthermore, vibration-assisted machining system is developed and applied to fabricate different materials to overcome some of the limitations of the AFM probe based single point nano mechanical machining. The novelty of this study includes the application of vibration-assisted AFM probe based nano scale machining to fabricate micro/nano scale features, calibration of an AFM by considering different factors, and the investigation of the nano scale material removal process from a different perspective.

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...

The nano-science of C60 molecule

International Nuclear Information System (INIS)

Rafii-Tabar, H.

2002-01-01

Over the past few years, nano-science and its associated nano-technology have emerged into prominence in research institutions across the world. They have brought about new scientific and engineering paradigms, allowing for the manipulation of single atoms and molecules, designing and fabricating new materials, atom-by-atom, and devices that operate on significantly reduced time and length scales. One important area of research in nano-science and nano technology is carbon-based physics in the form of fullerene physics. The C 6 0 molecule, and other cage-like fullerenes, together with carbon nano tubes provide objects that can be combined to generate three-dimensional functional structures for use in the anticipated nano-technology of future. The unique properties of C 6 0 can also be exploited in designing nano-phase thin films with applications in nano-scope device technology and processes such as nano-lithography. This requires a deep understanding of the highly complex process of adsorption of this molecule on a variety of substrates. We review the field of nano-scale nucleation and growth of C 6 0 molecules on some of the technologically important substrates. In addition to experimental results, the results of a set of highly accurate computational simulations are also reported

Nanomechanical mapping of graphene layers and interfaces in suspended graphene nanostructures grown via carbon diffusion

Energy Technology Data Exchange (ETDEWEB)

Robinson, B.J. [Department of Physics, Lancaster University, Lancaster LA1 4YB (United Kingdom); Rabot, C. [CEA-LETI-Minatec Campus, 17 rue des Martyrs, 38054 Grenoble Cedex 09 (France); Mazzocco, R. [Department of Physics, Lancaster University, Lancaster LA1 4YB (United Kingdom); Delamoreanu, A. [Microelectronics Technology Laboratory (LTM), Joseph Fourier University, French National Research Center (CNRS), 17 Avenue des Martyrs, 38054 Grenoble Cedex 9 (France); Zenasni, A. [CEA-LETI-Minatec Campus, 17 rue des Martyrs, 38054 Grenoble Cedex 09 (France); Kolosov, O.V., E-mail: o.kolosov@lancaster.ac.uk [Department of Physics, Lancaster University, Lancaster LA1 4YB (United Kingdom)

2014-01-01

Graphene's remarkable mechanical, electronic and thermal properties are strongly determined by both the mechanism of its growth and its interaction with the underlying substrate. Evidently, in order to explore the fundamentals of these mechanisms, efficient nanoscale methods that enable observation of features hidden underneath the immediate surface are needed. In this paper we use nanomechanical mapping via ultrasonic force microscopy that employs MHz frequency range ultrasonic vibrations and allows the observation of surface composition and subsurface interfaces with nanoscale resolution, to elucidate the morphology of few layer graphene (FLG) films produced via a recently reported method of carbon diffusion growth (CDG) on platinum-metal based substrate. CDG is known to result in FLG suspended over large areas, which could be of high importance for graphene transfer and applications where a standalone graphene film is required. This study directly reveals the detailed mechanism of CDG three-dimensional growth and FLG film detachment, directly linking the level of graphene decoupling with variations of the substrate temperature during the annealing phase of growth. We also show that graphene initially and preferentially decouples at the substrate grain boundaries, likely due to its negative expansion coefficient at cooling, forming characteristic “nano-domes” at the intersections of the grain boundaries. Furthermore, quantitative nanomechanical mapping of flexural stiffness of suspended FLG “nano-domes” using kHz frequency range force modulation microscopy uncovers the progression of “nano-dome” stiffness from single to bi-modal distribution as CDG growth progresses, suggesting growth instability at advanced CDG stages. - Highlights: • Exploring growth and film-substrate decoupling in carbon diffusion grown graphene • Nanomechanical mapping of few layer graphene and graphene–substrate interfaces • Quantitative stiffness mapping of

Systematic approach in optimizing numerical memory-bound kernels on GPU

KAUST Repository

Abdelfattah, Ahmad

2013-01-01

The use of GPUs has been very beneficial in accelerating dense linear algebra computational kernels (DLA). Many high performance numerical libraries like CUBLAS, MAGMA, and CULA provide BLAS and LAPACK implementations on GPUs as well as hybrid computations involving both, CPUs and GPUs. GPUs usually score better performance than CPUs for compute-bound operations, especially those characterized by a regular data access pattern. This paper highlights a systematic approach for efficiently implementing memory-bound DLA kernels on GPUs, by taking advantage of the underlying device\\'s architecture (e.g., high throughput). This methodology proved to outperform existing state-of-the-art GPU implementations for the symmetric matrix-vector multiplication (SYMV), characterized by an irregular data access pattern, in a recent work (Abdelfattah et. al, VECPAR 2012). We propose to extend this methodology to the general matrix-vector multiplication (GEMV) kernel. The performance results show that our GEMV implementation achieves better performance for relatively small to medium matrix sizes, making it very influential in calculating the Hessenberg and bidiagonal reductions of general matrices (radar applications), which are the first step toward computing eigenvalues and singular values, respectively. Considering small and medium size matrices (≤4500), our GEMV kernel achieves an average 60% improvement in single precision (SP) and an average 25% in double precision (DP) over existing open-source and commercial software solutions. These results improve reduction algorithms for both small and large matrices. The improved GEMV performances engender an averge 30% (SP) and 15% (DP) in Hessenberg reduction and up to 25% (SP) and 14% (DP) improvement for the bidiagonal reduction over the implementation provided by CUBLAS 5.0. © 2013 Springer-Verlag.

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.

Nano Trek Beyond: Driving Nanocars/Molecular Machines at Interfaces.

Science.gov (United States)

Ariga, Katsuhiko; Mori, Taizo; Nakanishi, Waka

2018-03-09

In 2016, the Nobel Prize in Chemistry was awarded for pioneering work on molecular machines. Half a year later, in Toulouse, the first molecular car race, a "nanocar race", was held by using the tip of a scanning tunneling microscope as an electrical remote control. In this Focus Review, we discuss the current state-of-the-art in research on molecular machines at interfaces. In the first section, we briefly explain the science behind the nanocar race, followed by a selection of recent examples of controlling molecules on surfaces. Finally, motion synchronization and the functions of molecular machines at liquid interfaces are discussed. This new concept of molecular tuning at interfaces is also introduced as a method for the continuous modification and optimization of molecular structure for target functions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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....

SVM Classifier – a comprehensive java interface for support vector machine classification of microarray data

Science.gov (United States)

Pirooznia, Mehdi; Deng, Youping

2006-01-01

Motivation Graphical user interface (GUI) software promotes novelty by allowing users to extend the functionality. SVM Classifier is a cross-platform graphical application that handles very large datasets well. The purpose of this study is to create a GUI application that allows SVM users to perform SVM training, classification and prediction. Results The GUI provides user-friendly access to state-of-the-art SVM methods embodied in the LIBSVM implementation of Support Vector Machine. We implemented the java interface using standard swing libraries. We used a sample data from a breast cancer study for testing classification accuracy. We achieved 100% accuracy in classification among the BRCA1–BRCA2 samples with RBF kernel of SVM. Conclusion We have developed a java GUI application that allows SVM users to perform SVM training, classification and prediction. We have demonstrated that support vector machines can accurately classify genes into functional categories based upon expression data from DNA microarray hybridization experiments. Among the different kernel functions that we examined, the SVM that uses a radial basis kernel function provides the best performance. The SVM Classifier is available at . PMID:17217518

Electron transport in nano-scaled piezoelectronic devices

Science.gov (United States)

Jiang, Zhengping; Kuroda, Marcelo A.; Tan, Yaohua; Newns, Dennis M.; Povolotskyi, Michael; Boykin, Timothy B.; Kubis, Tillmann; Klimeck, Gerhard; Martyna, Glenn J.

2013-05-01

The Piezoelectronic Transistor (PET) has been proposed as a post-CMOS device for fast, low-power switching. In this device, the piezoresistive channel is metalized via the expansion of a relaxor piezoelectric element to turn the device on. The mixed-valence compound SmSe is a good choice of PET channel material because of its isostructural pressure-induced continuous metal insulator transition, which is well characterized in bulk single crystals. Prediction and optimization of the performance of a realistic, nano-scaled PET based on SmSe requires the understanding of quantum confinement, tunneling, and the effect of metal interface. In this work, a computationally efficient empirical tight binding (ETB) model is developed for SmSe to study quantum transport in these systems and the scaling limit of PET channel lengths. Modulation of the SmSe band gap under pressure is successfully captured by ETB, and ballistic conductance shows orders of magnitude change under hydrostatic strain, supporting operability of the PET device at nanoscale.

Photo-nano immunotherapy for metastatic breast cancer using synergistic single-walled carbon nanotubes and glycated chitosan

Science.gov (United States)

Zhou, Feifan; Hasanjee, Aamr; Doughty, Austin; West, Connor; Liu, Hong; Chen, Wei R.

2015-03-01

In our previous work, we constructed a multifunctional nano system, using single-walled carbon nanotube (SWNT) and glycated chitosan (GC), which can synergize photothermal and immunological effects. To further confirm the therapy efficacy, with a metastatic mouse mammary tumor model (4T1), we investigate the therapy effects and immune response induced by SWNT-GC, under laser irradiation. Laser+SWNT-GC treatment not only suppressed the prime tumor, but also induced antitumor immune response. It could be developed into a promising treatment modality for the metastatic breast cancer.

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

Interface Testing for RTOS System Tasks based on the Run-Time Monitoring

International Nuclear Information System (INIS)

Sung, Ahyoung; Choi, Byoungju

2006-01-01

Safety critical embedded system requires high dependability of not only hardware but also software. It is intricate to modify embedded software once embedded. Therefore, it is necessary to have rigorous regulations to assure the quality of safety critical embedded software. IEEE V and V (Verification and Validation) process is recommended for software dependability, but a more quantitative evaluation method like software testing is necessary. In case of safety critical embedded software, it is essential to have a test that reflects unique features of the target hardware and its operating system. The safety grade PLC (Programmable Logic Controller) is a safety critical embedded system where hardware and software are tightly coupled. The PLC has HdS (Hardware dependent Software) and it is tightly coupled with RTOS (Real Time Operating System). Especially, system tasks that are tightly coupled with target hardware and RTOS kernel have large influence on the dependability of the entire PLC. Therefore, interface testing for system tasks that reflects the features of target hardware and RTOS kernel becomes the core of the PLC integration test. Here, we define interfaces as overlapped parts between two different layers on the system architecture. In this paper, we identify interfaces for system tasks and apply the identified interfaces to the safety grade PLC. Finally, we show the test results through the empirical study

Interface Testing for RTOS System Tasks based on the Run-Time Monitoring

Energy Technology Data Exchange (ETDEWEB)

Sung, Ahyoung; Choi, Byoungju [Ewha University, Seoul (Korea, Republic of)

2006-07-01

Safety critical embedded system requires high dependability of not only hardware but also software. It is intricate to modify embedded software once embedded. Therefore, it is necessary to have rigorous regulations to assure the quality of safety critical embedded software. IEEE V and V (Verification and Validation) process is recommended for software dependability, but a more quantitative evaluation method like software testing is necessary. In case of safety critical embedded software, it is essential to have a test that reflects unique features of the target hardware and its operating system. The safety grade PLC (Programmable Logic Controller) is a safety critical embedded system where hardware and software are tightly coupled. The PLC has HdS (Hardware dependent Software) and it is tightly coupled with RTOS (Real Time Operating System). Especially, system tasks that are tightly coupled with target hardware and RTOS kernel have large influence on the dependability of the entire PLC. Therefore, interface testing for system tasks that reflects the features of target hardware and RTOS kernel becomes the core of the PLC integration test. Here, we define interfaces as overlapped parts between two different layers on the system architecture. In this paper, we identify interfaces for system tasks and apply the identified interfaces to the safety grade PLC. Finally, we show the test results through the empirical study.

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

Directory of Open Access Journals (Sweden)

Hongzhi Wang

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

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

Science.gov (United States)

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

2016-01-01

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

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.

Nano-Electromechanical Systems: Displacement Detection and the Mechanical Single Electron Shuttle

Science.gov (United States)

Blick, R. H.; Beil, F. W.; Höhberger, E.; Erbe, A.; Weiss, C.

For an introduction to nano-electromechanical systems we present measurements on nanomechanical resonators operating in the radio frequency range. We discuss in detail two different schemes of displacement detection for mechanical resonators, namely conventional reflection measurements of a probing signal and direct detection by capacitive coupling via a gate electrode. For capacitive detection we employ an on-chip preamplifier, which enables direct measurements of the resonator's disp lacement. We observe that the mechanical quality factor of the resonator depends on the detection technique applied, which is verified in model calculations and report on the detection of sub-harmonics. In the second part we extend our investigations to include transport of single electrons through an electron island on the tip of a nanomachined mechanical pendulum. The pendulum is operated by applying a modulating electromagnetic field in the range of 1 - 200 MHz, leading to mechanical oscillations between two laterally integrated source and drain contacts. Forming tunneling barriers the metallic tip shuttles single electrons from source to drain. The resulting tunneling current shows distinct features corresponding to the discrete mechanical eigenfrequencies of the pendulum. We report on measurements covering the temperature range from 300 K down to 4.2 K. The transport properties of the device are compared in detail to model calculations based on a Master-equation approach.

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.

A Single Rod Multi-modality Multi-interface Level Sensor Using an AC Current Source

Directory of Open Access Journals (Sweden)

Abdulgader Hwili

2008-05-01

Full Text Available Crude oil separation is an important process in the oil industry. To make efficient use of the separators, it is important to know their internal behaviour, and to measure the levels of multi-interfaces between different materials, such as gas-foam, foam-oil, oil-emulsion, emulsion-water and water-solids. A single-rod multi-modality multi-interface level sensor is presented, which has a current source, and electromagnetic modalities. Some key issues have been addressed, including the effect of salt content and temperature i.e. conductivity on the measurement.

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

Synthesis of Boron Nano wires, Nano tubes, and Nano sheets

International Nuclear Information System (INIS)

Patel, R.B.; Chou, T.; Iqbal, Z.

2014-01-01

The synthesis of boron nano wires, nano tubes, and nano sheets using a thermal vapor deposition process is reported. This work confirms previous research and provides a new method capable of synthesizing boron nano materials. The materials were made by using various combinations of MgB 2 , Mg(BH 4 ) 2 , MCM-41, NiB, and Fe wire. Unlike previously reported methods, a nanoparticle catalyst and a silicate substrate are not required for synthesis. Two types of boron nano wires, boron nano tubes, and boron nano sheets were made. Their morphology and chemical composition were determined through the use of scanning electron microscopy, transmission electron microscopy, and electron energy loss spectroscopy. These boron-based materials have potential for electronic and hydrogen storage applications.

The nano-science of C sub 6 0 molecule

CERN Document Server

Rafii-Tabar, H

2002-01-01

Over the past few years, nano-science and its associated nano-technology have emerged into prominence in research institutions across the world. They have brought about new scientific and engineering paradigms, allowing for the manipulation of single atoms and molecules, designing and fabricating new materials, atom-by-atom, and devices that operate on significantly reduced time and length scales. One important area of research in nano-science and nano technology is carbon-based physics in the form of fullerene physics. The C sub 6 0 molecule, and other cage-like fullerenes, together with carbon nano tubes provide objects that can be combined to generate three-dimensional functional structures for use in the anticipated nano-technology of future. The unique properties of C sub 6 0 can also be exploited in designing nano-phase thin films with applications in nano-scope device technology and processes such as nano-lithography. This requires a deep understanding of the highly complex process of adsorption of thi...

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

International Nuclear Information System (INIS)

Damunir; Sri Rinanti Susilowati; Ariyani Kusuma Dewi

2015-01-01

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

A nano lamella NbTi–NiTi composite with high strength

Energy Technology Data Exchange (ETDEWEB)

Jiang, Jiang [Jiangxi Key Laboratory of Advanced Copper and Tungsten Materials, Jiangxi Academy of Sciences, Nanchang 330029 (China); Institute of Applied Physics of Jiangxi Academy of Sciences, Nanchang 330029 (China); State Key Laboratory of Heavy Oil Processing and Department of Materials Science and engineering, China University of Petroleum, Beijing 102249 (China); Jiang, Daqiang [State Key Laboratory of Heavy Oil Processing and Department of Materials Science and engineering, China University of Petroleum, Beijing 102249 (China); School of Mechanical and Chemical Engineering, The University of Western Australia, WA 6009 (Australia); Hao, Shijie; Yu, Cun; Zhang, Junsong [State Key Laboratory of Heavy Oil Processing and Department of Materials Science and engineering, China University of Petroleum, Beijing 102249 (China); Ren, Yang [X-ray Science Division, Argonne National Laboratory, Argonne, IL 60439 (United States); Lu, Deping; Xie, Shifang [Jiangxi Key Laboratory of Advanced Copper and Tungsten Materials, Jiangxi Academy of Sciences, Nanchang 330029 (China); Institute of Applied Physics of Jiangxi Academy of Sciences, Nanchang 330029 (China); Cui, Lishan, E-mail: lishancui63@126.com [State Key Laboratory of Heavy Oil Processing and Department of Materials Science and engineering, China University of Petroleum, Beijing 102249 (China)

2015-05-01

A hypereutectic Nb{sub 60}Ti{sub 24}Ni{sub 16} (at%) alloy was prepared by vacuum induction melting, and a nano lamellae NbTi–NiTi composite was obtained by hot-forging and wire-drawing of the ingot. Microscopic analysis showed that NbTi and NiTi nano lamellae distributed alternatively in the composite, and aligned along the wire axial direction, with a high volume fraction (~70%) of NbTi nano lamellae. In situ synchrotron X-ray diffraction analysis revealed that stress induced martensitic transformation occurred upon loading, which would effectively weaken the stress concentration at the interface and avoid the introduction of defects into the nano reinforced phase. Then the embedded NbTi nano lamellae exhibited a high elastic strain up to 2.72%, 1.5 times as high as that of the Nb nanowires embedded in a conventional plastic matrix, and the corresponding stress carried by NbTi was evaluated as 2.53 GPa. The high volume fraction of NbTi nano lamellae improved the translation of high strength from the nano reinforced phase into bulk properties of the composite, with a platform stress of ~1.7 GPa and a fracture strength of ~1.9 GPa.

Tipping solutions: emerging 3D nano-fabrication/ -imaging technologies

Directory of Open Access Journals (Sweden)

Seniutinas Gediminas

2017-06-01

Full Text Available The evolution of optical microscopy from an imaging technique into a tool for materials modification and fabrication is now being repeated with other characterization techniques, including scanning electron microscopy (SEM, focused ion beam (FIB milling/imaging, and atomic force microscopy (AFM. Fabrication and in situ imaging of materials undergoing a three-dimensional (3D nano-structuring within a 1−100 nm resolution window is required for future manufacturing of devices. This level of precision is critically in enabling the cross-over between different device platforms (e.g. from electronics to micro-/nano-fluidics and/or photonics within future devices that will be interfacing with biological and molecular systems in a 3D fashion. Prospective trends in electron, ion, and nano-tip based fabrication techniques are presented.

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...

Growth of VO2 Nano wires from Supercooled Liquid Nano droplets and E-beam Irradiation for Ultra-sensitive sensor

International Nuclear Information System (INIS)

Byun, Ji Won; Baik, Jeong Min; Lee, Sang Hyun; Lee, Byung Cheol

2011-01-01

Vanadium dioxide is an interesting material on account of its easily accessible and sharp Mott metal-insulator transition at ∼ 68 .deg. C in the bulk, which is of great interest in sensing and catalytic applications. In this Paper, we describe the synthesis and properties of VO 2 nano wires as novel catalytic and gas sensor materials based on electron beam irradiation. High yields of single crystalline VO 2 nano wires are synthesized by atmospheric-pressure, physical vapor deposition using V 2 O 5 layer. Pd-decorated VO 2 nano wire sensors show extraordinary sensitivity towards hydrogen, an almost 3 order-of-magnitude increase in the current through the nano wire. By the Eb irradiation, the conductance of the nano wires significantly increased up to 5 times, reducing the response time by half and the operating temperature. The metal nanoparticles-VO 2 nano wire system will be very promising for high-sensitivity and high-selectivity under low temperature less than 100. deg. C

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.

Performance enhancement of quantum dot-sensitized solar cells based on polymer nano-composite catalyst

International Nuclear Information System (INIS)

Seo, Hyunwoong; Gopi, Chandu V.V.M.; Kim, Hee-Je; Itagaki, Naho; Koga, Kazunori; Shiratani, Masaharu

2017-01-01

Highlights: •We studied polymer nano-composite containing TiO 2 nano-particles as a catalyst. •Polymer nano-composite was applied for quantum dot-sensitized solar cells. •Polymer nano-composite catalyst was considerably improved with TiO 2 nano-particles. •Polymer nano-composite showed higher photovoltaic performance than conventional Au. -- Abstract: Polymer nano-composite composed of poly(3,4-ethylenedioxythiophene):poly (styrenesulfonate) and TiO 2 nano-particles was deposited on fluorine-doped tin oxide substrate and applied as an alternative to Au counter electrode of quantum dot-sensitized solar cell (QDSC). It became surface-richer with the increase in nano-particle amount so that catalytic reaction was increased by widened catalytic interface. Electrochemical impedance spectroscopy and cyclic voltammetry clearly demonstrated the enhancement of polymer nano-composite counter electrode. A QDSC based on polymer nano-composite counter electrode showed 0.56 V of V OC , 12.24 mA cm −2 of J SC , 0.57 of FF, and 3.87% of efficiency and this photovoltaic performance was higher than that of QDSC based on Au counter electrode (3.75%).

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.

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....

Nano-technology and nano-toxicology.

Science.gov (United States)

Maynard, Robert L

2012-01-01

Rapid developments in nano-technology are likely to confer significant benefits on mankind. But, as with perhaps all new technologies, these benefits are likely to be accompanied by risks, perhaps by new risks. Nano-toxicology is developing in parallel with nano-technology and seeks to define the hazards and risks associated with nano-materials: only when risks have been identified they can be controlled. This article discusses the reasons for concern about the potential effects on health of exposure to nano-materials and relates these to the evidence of the effects on health of the ambient aerosol. A number of hypotheses are proposed and the dangers of adopting unsubstantiated hypotheses are stressed. Nano-toxicology presents many challenges and will need substantial financial support if it is to develop at a rate sufficient to cope with developments in nano-technology.

Nano-Gap Embedded Plasmonic Gratings for Surface Plasmon Enhanced Fluorescence

Science.gov (United States)

Bhatnagar, Kunal; Bok, Sangho; Korampally, Venumadhav; Gangopadhyay, Shubhra

2012-02-01

Plasmonic nanostructures have been extensively used in the past few decades for applications in sub-wavelength optics, data storage, optoelectronic circuits, microscopy and bio-photonics. The enhanced electromagnetic field produced at the metal/dielectric interface by the excitation of surface plasmons via incident radiation can be used for signal enhancement in fluorescence and surface enhanced Raman scattering studies. Novel plasmonic structures on the sub wavelength scale have been shown to provide very efficient and extreme light concentration at the nano-scale. The enhanced electric field produced within a few hundred nanometers of these structures can be used to excite fluorophores in the surrounding environment. Fluorescence based bio-detection and bio-imaging are two of the most important tools in the life sciences. Improving the qualities and capabilities of fluorescence based detectors and imaging equipment has been a big challenge to the industry manufacturers. We report the novel fabrication of nano-gap embedded periodic grating substrates on the nanoscale using micro-contact printing and polymethylsilsesquioxane (PMSSQ) polymer. Fluorescence enhancement of up to 118 times was observed with these silver nanostructures in conjugation with Rhodamine-590 fluorescent dye. These substrates are ideal candidates for low-level fluorescence detection and single molecule imaging.

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.

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....

Observation of terahertz-radiation-induced ionization in a single nano island.

Science.gov (United States)

Seo, Minah; Kang, Ji-Hun; Kim, Hyo-Suk; Hyong Cho, Joon; Choi, Jaebin; Min Jhon, Young; Lee, Seok; Hun Kim, Jae; Lee, Taikjin; Park, Q-Han; Kim, Chulki

2015-05-22

Terahertz (THz) electromagnetic wave has been widely used as a spectroscopic probe to detect the collective vibrational mode in vast molecular systems and investigate dielectric properties of various materials. Recent technological advances in generating intense THz radiation and the emergence of THz plasmonics operating with nanoscale structures have opened up new pathways toward THz applications. Here, we present a new opportunity in engineering the state of matter at the atomic scale using THz wave and a metallic nanostructure. We show that a medium strength THz radiation of 22 kV/cm can induce ionization of ambient carbon atoms through interaction with a metallic nanostructure. The prepared structure, made of a nano slot antenna and a nano island located at the center, acts as a nanogap capacitor and enhances the local electric field by two orders of magnitudes thereby causing the ionization of ambient carbon atoms. Ionization and accumulation of carbon atoms are also observed through the change of the resonant condition of the nano slot antenna and the shift of the characteristic mode in the spectrum of the transmitted THz waves.

Analysis of the traveltime sensitivity kernels for an acoustic transversely isotropic medium with a vertical axis of symmetry

KAUST Repository

Djebbi, Ramzi

2016-02-05

In anisotropic media, several parameters govern the propagation of the compressional waves. To correctly invert surface recorded seismic data in anisotropic media, a multi-parameter inversion is required. However, a tradeoff between parameters exists because several models can explain the same dataset. To understand these tradeoffs, diffraction/reflection and transmission-type sensitivity-kernels analyses are carried out. Such analyses can help us to choose the appropriate parameterization for inversion. In tomography, the sensitivity kernels represent the effect of a parameter along the wave path between a source and a receiver. At a given illumination angle, similarities between sensitivity kernels highlight the tradeoff between the parameters. To discuss the parameterization choice in the context of finite-frequency tomography, we compute the sensitivity kernels of the instantaneous traveltimes derived from the seismic data traces. We consider the transmission case with no encounter of an interface between a source and a receiver; with surface seismic data, this corresponds to a diving wave path. We also consider the diffraction/reflection case when the wave path is formed by two parts: one from the source to a sub-surface point and the other from the sub-surface point to the receiver. We illustrate the different parameter sensitivities for an acoustic transversely isotropic medium with a vertical axis of symmetry. The sensitivity kernels depend on the parameterization choice. By comparing different parameterizations, we explain why the parameterization with the normal moveout velocity, the anellipitic parameter η, and the δ parameter is attractive when we invert diving and reflected events recorded in an active surface seismic experiment. © 2016 European Association of Geoscientists & Engineers.

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

Advances in single chain technology.

Science.gov (United States)

Gonzalez-Burgos, Marina; Latorre-Sanchez, Alejandro; Pomposo, José A

2015-10-07

The recent ability to manipulate and visualize single atoms at atomic level has given rise to modern bottom-up nanotechnology. Similar exquisite degree of control at the individual polymeric chain level for producing functional soft nanoentities is expected to become a reality in the next few years through the full development of so-called "single chain technology". Ultra-small unimolecular soft nano-objects endowed with useful, autonomous and smart functions are the expected, long-term valuable output of single chain technology. This review covers the recent advances in single chain technology for the construction of soft nano-objects via chain compaction, with an emphasis in dynamic, letter-shaped and compositionally unsymmetrical single rings, complex multi-ring systems, single chain nanoparticles, tadpoles, dumbbells and hairpins, as well as the potential end-use applications of individual soft nano-objects endowed with useful functions in catalysis, sensing, drug delivery and other uses.

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

Science.gov (United States)

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

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

Predictive Model Equations for Palm Kernel (Elaeis guneensis J ...

African Journals Online (AJOL)

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

Heat kernel analysis for Bessel operators on symmetric cones

DEFF Research Database (Denmark)

Möllers, Jan

2014-01-01

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

A multi-scale kernel bundle for LDDMM

DEFF Research Database (Denmark)

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

2011-01-01

The Large Deformation Diffeomorphic Metric Mapping framework constitutes a widely used and mathematically well-founded setup for registration in medical imaging. At its heart lies the notion of the regularization kernel, and the choice of kernel greatly affects the results of registrations...

New KF-PP-SVM classification method for EEG in brain-computer interfaces.

Science.gov (United States)

Yang, Banghua; Han, Zhijun; Zan, Peng; Wang, Qian

2014-01-01

Classification methods are a crucial direction in the current study of brain-computer interfaces (BCIs). To improve the classification accuracy for electroencephalogram (EEG) signals, a novel KF-PP-SVM (kernel fisher, posterior probability, and support vector machine) classification method is developed. Its detailed process entails the use of common spatial patterns to obtain features, based on which the within-class scatter is calculated. Then the scatter is added into the kernel function of a radial basis function to construct a new kernel function. This new kernel is integrated into the SVM to obtain a new classification model. Finally, the output of SVM is calculated based on posterior probability and the final recognition result is obtained. To evaluate the effectiveness of the proposed KF-PP-SVM method, EEG data collected from laboratory are processed with four different classification schemes (KF-PP-SVM, KF-SVM, PP-SVM, and SVM). The results showed that the overall average improvements arising from the use of the KF-PP-SVM scheme as opposed to KF-SVM, PP-SVM and SVM schemes are 2.49%, 5.83 % and 6.49 % respectively.

Advanced vectorial simulation of VCSELs with nano structures invited paper

DEFF Research Database (Denmark)

Chung, Il-Sug; Mørk, Jesper

2009-01-01

The single-mode properties and design issues of three vertical-cavity surface-emitting laser (VCSEL) structures incorporating nano structures are rigorously investigated. Nano structuring enables to deliver selective pumping or loss to the fundamental mode as well as stabilizing the output...... polarization state. Comparison of three vectorial simulation methods reveals that the modal expansion method is suitable for treating the nano structured VCSEL designs....

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.

Nano-structural characteristics and optical properties of silver chiral nano-flower sculptured thin films

Energy Technology Data Exchange (ETDEWEB)

Savaloni, Hadi, E-mail: savaloni@khayam.ut.ac.ir [Department of Physics, University of Tehran, North-Kargar Street, Tehran (Iran, Islamic Republic of); Haydari-Nasab, Fatemh; Malmir, Mariam [Department of Physics, University of Tehran, North-Kargar Street, Tehran (Iran, Islamic Republic of)

2011-08-15

Silver chiral nano-flowers with 3-, 4- and 5-fold symmetry were produced using oblique angle deposition method in conjunction with the rotation of sample holder with different speeds at different sectors of each revolution corresponding to symmetry order of the acquired nano-flower. Atomic force microscopy (AFM) and field emission scanning electron microscopy (FESEM), were employed to obtain morphology and nano-structure of the films. Optical characteristics of silver chiral nano-flower thin films were obtained using single beam spectrophotometer with both s- and p-polarization incident light at 30{sup o} and 70{sup o} incidence angles and at different azimuthal angles ({phi}). Optical spectra showed both TM (TDM (transverse dipole mode) and TQM (transverse quadruple mode)) and LM (longitudinal mode) Plasmon resonance peaks. For 3- and 4-fold symmetry chiral nano-flowers the s-polarization extinction spectra obtained at different azimuthal angles did not show significant change in the Plasmon peak position while 5-fold symmetry chiral nano-flower showed a completely different behavior, which may be the result of increased surface anisotropy, so when the {phi} angle is changed the s-polarization response from the surface can change more significantly than that for lower symmetries. In general, for 3-, 4- and 5-fold symmetry chiral nano-flowers a sharp peak at lower wavelengths (<450 nm) is observed in the s-polarization spectra, while in addition to this peak a broad peak at longer wavelengths (i.e., LM) observed in the p-polarization spectra, which is more dominant for 70{sup o} incidence angle.

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.

Synthesis and bio-evaluation of nano-hydroxyapatite trapped by 153Sm

International Nuclear Information System (INIS)

Bing Wenzeng; Luo Shunzhong; Wen Guanghua; Jiang Shubin; Xiong Xiaoling; Liu Guoping

2006-03-01

After nanoHA was synthesized, 153 Sm-EDTMP-nanoHA and 153 Sm-citrate-nanoHA were prepared and proved stable in vitro. ECT images of New Zealand rabbits injected with 153 Sm-EDTMP-nanoHA had better contrast, skeletal figure visible, liver and spleen clear. The images of 153 Sm-citrate-nanoHA showed a similar results but kidney invisible, which meant 153 Sm-citrate-nanoHA showed a similar results but kidney invisible, which meant 153 Sm-citrate-nanoHA was mainly excreted through liver and gall. 153 Sm-EDTMP-nanoHA's half effective inhibition concentrations to SMMC-7721 and MCF-7 cells were 1.98 g/L and 0.075 g/L respectively and 153 Sm-citrate-nanoHA's were 1.89 g/L and 0.094 g/L proportionally. 153 Sm-EDTMP-nanoHA and 153 Sm-citrate-nanoHA were worthy of a further research because their half effective inhibition concentrations were much lower than ones of the single nanoHA. (authors)

Gas selectivity of SILAR grown CdS nano-bulk junction

Science.gov (United States)

Jayakrishnan, R.; Nair, Varun G.; Anand, Akhil M.; Venugopal, Meera

2018-03-01

Nano-particles of cadmium sulphide were deposited on cleaned copper substrate by an automated sequential ionic layer adsorption reaction (SILAR) system. The grown nano-bulk junction exhibits Schottky diode behavior. The response of the nano-bulk junction was investigated under oxygen and hydrogen atmospheric conditions. The gas response ratio was found to be 198% for Oxygen and 34% for Hydrogen at room temperature. An increase in the operating temperature of the nano-bulk junction resulted in a decrease in their gas response ratio. A logarithmic dependence on the oxygen partial pressure to the junction response was observed, indicating a Temkin isothermal behavior. Work function measurements using a Kelvin probe demonstrate that the exposure to an oxygen atmosphere fails to effectively separate the charges due to the built-in electric field at the interface. Based on the benefits like simple structure, ease of fabrication and response ratio the studied device is a promising candidate for gas detection applications.

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

Nano technology

International Nuclear Information System (INIS)

Lee, In Sik

2002-03-01

This book is introduction of nano technology, which describes what nano technology is, alpha and omega of nano technology, the future of Korean nano technology and human being's future and nano technology. The contents of this book are nano period is coming, a engine of creation, what is molecular engineering, a huge nano technology, technique on making small things, nano materials with exorbitant possibility, the key of nano world the most desirable nano technology in bio industry, nano development plan of government, the direction of development for nano technology and children of heart.

Auger electron spectroscopy analysis for growth interface of cubic boron nitride single crystals synthesized under high pressure and high temperature

Science.gov (United States)

Lv, Meizhe; Xu, Bin; Cai, Lichao; Guo, Xiaofei; Yuan, Xingdong

2018-05-01

After rapid cooling, cubic boron nitride (c-BN) single crystals synthesized under high pressure and high temperature (HPHT) are wrapped in the white film powders which are defined as growth interface. In order to make clear that the transition mechanism of c-BN single crystals, the variation of B and N atomic hybrid states in the growth interface is analyzed with the help of auger electron spectroscopy in the Li-based system. It is found that the sp2 fractions of B and N atoms decreases, and their sp3 fractions increases from the outer to the inner in the growth interface. In addition, Lithium nitride (Li3N) are not found in the growth interface by X-ray diffraction (XRD) experiment. It is suggested that lithium boron nitride (Li3BN2) is produced by the reaction of hexagonal boron nitride (h-BN) and Li3N at the first step, and then B and N atoms transform from sp2 into sp3 state with the catalysis of Li3BN2 in c-BN single crystals synthesis process.

Interface inductive currents and carrier injection in hybrid perovskite single crystals

Science.gov (United States)

Kovalenko, Alexander; Pospisil, Jan; Krajcovic, Jozef; Weiter, Martin; Guerrero, Antonio; Garcia-Belmonte, Germà

2017-10-01

Interfaces between the absorbing perovskite and transporting layers are gaining attention as the key locus that governs solar cell operation and long term performance. The interplay of ionic and electronic processes, along with the asymmetrical architecture of any solar cell, makes the interpretation of electrical measurements always inconclusive. A strategy to progress in relating electric responses, operating mechanisms, and device architecture relies upon simplifying the probing structure. Macroscopic CH3NH3PbBr3 single crystals with symmetrical contacts are tested by means of long-time current transient and impedance spectroscopy. It is observed that interfaces govern carrier injection to (and extraction from) perovskite layers through an inductive (negative capacitance) mechanism with a response time in the range of ˜ 1 - 100 s under dark conditions and inert atmosphere. Current transient exhibits a slow recovering after the occurrence of an undershoot, signaling a complex carrier dynamics which involves changes in surface state occupancy.

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...

Large Scale Plasmonic nanoCones array For Spectroscopy Detection

KAUST Repository

Das, Gobind

2015-09-24

Advanced optical materials or interfaces are gaining attention for diagnostic applications. However, the achievement of large device interface as well as facile surface functionalization largely impairs their wide use. The present work is aimed to address different innovative aspects related to the fabrication of large area 3D plasmonic arrays, their direct and easy functionalization with capture elements and their spectroscopic verifications through enhanced Raman and enhanced fluorescence techniques. In detail we have investigated the effect of Au-based nanoCones array, fabricated by means of direct nanoimprint technique over large area (mm2), on protein capturing and on the enhancement in optical signal. A selective functionalization of gold surfaces was proposed by using a peptide (AuPi3) previously selected by phage display. In this regard, two different sequences, labeled with fluorescein and biotin, were chemisorbed on metallic surfaces. The presence of Au nanoCones array consents an enhancement in electric field on the apex of cone, enabling the detection of molecules. We have witnessed around 12-fold increase in fluorescence intensity and SERS enhancement factor around 1.75 ×105 with respect to the flat gold surface. Furthermore, a sharp decrease in fluorescence lifetime over nanoCones confirms the increase in radiative emission (i.e. an increase in photonics density at the apex of cones).