Sparse Parallel MRI Based on Accelerated Operator Splitting Schemes
Xie, Weisi; Su, Zhenghang
2016-01-01
Recently, the sparsity which is implicit in MR images has been successfully exploited for fast MR imaging with incomplete acquisitions. In this paper, two novel algorithms are proposed to solve the sparse parallel MR imaging problem, which consists of l1 regularization and fidelity terms. The two algorithms combine forward-backward operator splitting and Barzilai-Borwein schemes. Theoretically, the presented algorithms overcome the nondifferentiable property in l1 regularization term. Meanwhile, they are able to treat a general matrix operator that may not be diagonalized by fast Fourier transform and to ensure that a well-conditioned optimization system of equations is simply solved. In addition, we build connections between the proposed algorithms and the state-of-the-art existing methods and prove their convergence with a constant stepsize in Appendix. Numerical results and comparisons with the advanced methods demonstrate the efficiency of proposed algorithms. PMID:27746824
Shaping light with split lens configurations
NASA Astrophysics Data System (ADS)
Lizana, A.; Vargas, A.; Turpin, A.; Ramirez, C.; Estevez, I.; Campos, J.
2016-10-01
We present an intuitive and versatile method that can dynamically generate 2D and 3D tailored light patterns. The light structures are generated by dynamically implementing discrete and continuous split lens configurations onto a spatial light modulator. These configurations can be dynamically modified by tuning a reduced number of control parameters with simple physical interpretation. We demonstrate the versatility of the method by experimentally implementing a wide number of structured beams, including optical lattices, a light cone, and vortex beams carrying orbital angular momentum. Compared with other optical illuminators, the advantages of our method are its simple interpretation and control for creating the light structures, and that it is based on a robust, dynamic and easy-to-build optical set-up. The proposed method may be useful in a large number of applications, such as optical trapping, super-resolution imaging or illuminating arrays of photonic switching devices.
Light-activated Reassembly of Split GFP
Kent, Kevin P.; Boxer, Steven G.
2011-01-01
Truncated Green Fluorescent Protein (GFP) with the 11th β-strand removed is potentially interesting for bioconjugation, imaging, and the preparation of semi-synthetic proteins with novel spectroscopic or functional properties. Surprisingly, the truncated GFP generated by removing the 11th strand, once refolded, does not reassemble with a synthetic peptide corresponding to strand 11, but does reassemble following light activation. The mechanism of this process has been studied in detail by absorption, fluorescence and Raman spectroscopy. The chromophore in this refolded truncated GFP is found to be in the trans configuration. Upon exposure to light a photostationary state is formed between the trans and cis conformations of the chromophore, and only truncated GFP with the cis configuration of the chromophore binds the peptide. A kinetic model describing the light activated reassembly of this split GFP is discussed. This unique light-driven reassembly is potentially useful for controlling protein-protein interactions. PMID:21351768
Huang, Lei; Jin, Yan; Gao, Yaozong; Thung, Kim-Han; Shen, Dinggang
2016-10-01
Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies, machine learning techniques have shown promising results on the prediction of AD clinical scores. However, there are multiple limitations in the current models such as linearity assumption and missing data exclusion. Here, we present a nonlinear supervised sparse regression-based random forest (RF) framework to predict a variety of longitudinal AD clinical scores. Furthermore, we propose a soft-split technique to assign probabilistic paths to a test sample in RF for more accurate predictions. In order to benefit from the longitudinal scores in the study, unlike the previous studies that often removed the subjects with missing scores, we first estimate those missing scores with our proposed soft-split sparse regression-based RF and then utilize those estimated longitudinal scores at all the previous time points to predict the scores at the next time point. The experiment results demonstrate that our proposed method is superior to the traditional RF and outperforms other state-of-art regression models. Our method can also be extended to be a general regression framework to predict other disease scores. PMID:27500865
Light splitting in nanoporous gold and silver.
Bosman, Michel; Anstis, Geoffrey R; Keast, Vicki J; Clarke, Jackson D; Cortie, Michael B
2012-01-24
Nanoporous gold and silver exhibit strong, omnidirectional broad-band absorption in the far-field. Even though they consist entirely of gold or silver atoms, these materials appear black and dull, in great contrast with the familiar luster of continuous gold and silver. The nature of these anomalous optical characteristics is revealed here by combining nanoscale electron energy loss spectroscopy with discrete dipole and boundary element simulations. It is established that the strong broad-band absorption finds its origin in nanoscale splitting of light, with great local variations in the absorbed color. This nanoscale polychromaticity results from the excitation of localized surface plasmon resonances, which are imaged and analyzed here with deep sub-wavelength, nanometer spatial resolution. We demonstrate that, with this insight, it is possible to customize the absorbance and reflectance wavelength bands of thin nanoporous films by only tuning their morphology.
Muon loop light-by-light contribution to hyperfine splitting in muonium.
Eides, Michael I; Shelyuto, Valery A
2014-05-01
Three-loop corrections to hyperfine splitting in muonium, generated by the gauge-invariant sets of diagrams with muon and tauon loop light-by-light scattering blocks, are calculated. These results complete calculations of all light-by-light scattering contributions to hyperfine splitting in muonium.
Hadronic light-by-light scattering in muonium hyperfine splitting
Karshenboim, S. G.; Shelyuto, V. A.; Vainshtein, A. I.
2008-09-15
We consider an impact of hadronic light-by-light scattering on the muonium hyperfine structure. A shift of the hyperfine interval {delta}{nu}(Mu){sub HLBL} is calculated with the light-by-light scattering approximated by the exchange of pseudoscalar and pseudovector mesons. Constraints from the operator product expansion in QCD are used to fix parameters of the model similar to the one used earlier for the hadronic light-by-light scattering in calculations of the muon anomalous magnetic moment. The pseudovector exchange is dominant in the resulting shift, {delta}{nu}(Mu){sub HLBL}=-0.0065(10) Hz. Although the effect is tiny it is useful in understanding the level of hadronic uncertainties.
Visible light water splitting using dye-sensitized oxide semiconductors.
Youngblood, W Justin; Lee, Seung-Hyun Anna; Maeda, Kazuhiko; Mallouk, Thomas E
2009-12-21
Researchers are intensively investigating photochemical water splitting as a means of converting solar to chemical energy in the form of fuels. Hydrogen is a key solar fuel because it can be used directly in combustion engines or fuel cells, or combined catalytically with CO(2) to make carbon containing fuels. Different approaches to solar water splitting include semiconductor particles as photocatalysts and photoelectrodes, molecular donor-acceptor systems linked to catalysts for hydrogen and oxygen evolution, and photovoltaic cells coupled directly or indirectly to electrocatalysts. Despite several decades of research, solar hydrogen generation is efficient only in systems that use expensive photovoltaic cells to power water electrolysis. Direct photocatalytic water splitting is a challenging problem because the reaction is thermodynamically uphill. Light absorption results in the formation of energetic charge-separated states in both molecular donor-acceptor systems and semiconductor particles. Unfortunately, energetically favorable charge recombination reactions tend to be much faster than the slow multielectron processes of water oxidation and reduction. Consequently, visible light water splitting has only recently been achieved in semiconductor-based photocatalytic systems and remains an inefficient process. This Account describes our approach to two problems in solar water splitting: the organization of molecules into assemblies that promote long-lived charge separation, and catalysis of the electrolysis reactions, in particular the four-electron oxidation of water. The building blocks of our artificial photosynthetic systems are wide band gap semiconductor particles, photosensitizer and electron relay molecules, and nanoparticle catalysts. We intercalate layered metal oxide semiconductors with metal nanoparticles. These intercalation compounds, when sensitized with [Ru(bpy)(3)](2+) derivatives, catalyze the photoproduction of hydrogen from sacrificial
NASA Astrophysics Data System (ADS)
Kumar, U.; Milesi, C.; Nemani, R. R.; Raja, S. Kumar; Ganguly, S.; Wang, W.
2015-06-01
In this paper, we explore the possibility of sparse regression, a new direction in unmixing, for vegetation and urban area classification. SUnSAL (Sparse unmixing via variable splitting and augmented Lagrangian) in both unconstrained and constrained forms (with the abundance non-negativity and abundance sum-to-one constraints) were used with a set of global endmembers (substrate, vegetation and dark objects) to unmix a set of computer simulated noise-free and noisy data (with Gaussian noise of different signal-to-noise ratio) in order to judge the robustness of the algorithm. The error in the fractional estimate was examined for varying noise power (variance): 2, 4, 8, 16, 32, 64, 128 and 256. In the second set of experiments, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data representing an agricultural setup in Fresno, California, USA were used. The corresponding ground data for validation were collected on the same days of satellite overpass. Finally in the third set of experiments, a clear sky Landsat-5 TM data for an area near the Golden Gate Bridge, San Francisco (an urbanized landscape), California, USA were used to assess the algorithm. The fractional estimates of the 30 m Landsat-5 TM data were compared with the fractional estimates of a high-resolution World View-2 data (2 m spatial resolution) obtained using a fully constrained least squares algorithm. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success and bivariate distribution function, which showed that constrained model was better than unconstrained form.
Water splitting on semiconductor catalysts under visible-light irradiation.
Navarro Yerga, Rufino M; Alvarez Galván, M Consuelo; del Valle, F; Villoria de la Mano, José A; Fierro, José L G
2009-01-01
Sustainable hydrogen production is a key target for the development of alternative, future energy systems that will provide a clean and affordable energy supply. The Sun is a source of silent and precious energy that is distributed fairly all over the Earth daily. However, its tremendous potential as a clean, safe, and economical energy source cannot be exploited unless the energy is accumulated or converted into more useful forms. The conversion of solar energy into hydrogen via the water-splitting process, assisted by photo-semiconductor catalysts, is one of the most promising technologies for the future because large quantities of hydrogen can potentially be generated in a clean and sustainable manner. This Minireview provides an overview of the principles, approaches, and research progress on solar hydrogen production via the water-splitting reaction on photo-semiconductor catalysts. It presents a survey of the advances made over the last decades in the development of catalysts for photochemical water splitting under visible-light irradiation. The Minireview also analyzes the energy requirements and main factors that determine the activity of photocatalysts in the conversion of water into hydrogen and oxygen using sunlight. Remarkable progress has been made since the pioneering work by Fujishima and Honda in 1972, but he development of photocatalysts with improved efficiencies for hydrogen production from water using solar energy still faces major challenges. Research strategies and approaches adopted in the search for active and efficient photocatalysts, for example through new materials and synthesis methods, are presented and analyzed.
Robust and accurate transient light transport decomposition via convolutional sparse coding.
Hu, Xuemei; Deng, Yue; Lin, Xing; Suo, Jinli; Dai, Qionghai; Barsi, Christopher; Raskar, Ramesh
2014-06-01
Ultrafast sources and detectors have been used to record the time-resolved scattering of light propagating through macroscopic scenes. In the context of computational imaging, decomposition of this transient light transport (TLT) is useful for applications, such as characterizing materials, imaging through diffuser layers, and relighting scenes dynamically. Here, we demonstrate a method of convolutional sparse coding to decompose TLT into direct reflections, inter-reflections, and subsurface scattering. The method relies on the sparsity composition of the time-resolved kernel. We show that it is robust and accurate to noise during the acquisition process.
Diffraction-dependent spin splitting in spin Hall effect of light on reflection.
Qiu, Xiaodong; Xie, Linguo; Qiu, Jiangdong; Zhang, Zhiyou; Du, Jinglei; Gao, Fuhua
2015-07-27
We report on a diffraction-dependent spin splitting of the paraxial Gaussian light beams on reflection theoretically and experimentally. In the case of horizontal incident polarization, the spin splitting is proportional to the diffraction length of light beams near the Brewster angle. However, the spin splitting is nearly independent with the diffraction length for the vertical incident polarization. By means of the angular spectrum theory, we find that the diffraction-dependent spin splitting is attributed to the first order expansion term of the reflection coefficients with respect to the transverse wave-vector which is closely related to the diffraction length.
Plasmonic photoanodes for solar water splitting with visible light.
Lee, Joun; Mubeen, Syed; Ji, Xiulei; Stucky, Galen D; Moskovits, Martin
2012-09-12
We report a plasmonic water splitting cell in which 95% of the effective charge carriers derive from surface plasmon decay to hot electrons, as evidenced by fuel production efficiencies up to 20-fold higher at visible, as compared to UV, wavelengths. The cell functions by illuminating a dense array of aligned gold nanorods capped with TiO(2), forming a Schottky metal/semiconductor interface which collects and conducts the hot electrons to an unilluminated platinum counter-electrode where hydrogen gas evolves. The resultant positive charges in the Au nanorods function as holes and are extracted by an oxidation catalyst which electrocatalytically oxidizes water to oxygen gas.
NASA Astrophysics Data System (ADS)
Konoshonkin, Alexander V.; Kustova, Natalia V.; Borovoi, Anatoli G.
2015-10-01
The open-source beam-splitting code is described which implements the geometric-optics approximation to light scattering by convex faceted particles. This code is written in C++ as a library which can be easy applied to a particular light scattering problem. The code uses only standard components, that makes it to be a cross-platform solution and provides its compatibility to popular Integrated Development Environments (IDE's). The included example of solving the light scattering by a randomly oriented ice crystal is written using Qt 5.1, consequently it is a cross-platform solution, too. Both physical and computational aspects of the beam-splitting algorithm are discussed. Computational speed of the beam-splitting code is obviously higher compared to the conventional ray-tracing codes. A comparison of the phase matrix as computed by our code with the ray-tracing code by A. Macke shows excellent agreement.
Optical power splitter for splitting high power light
English, Jr., Ronald E.; Christensen, John J.
1995-01-01
An optical power splitter for the distribution of high-power light energy has a plurality of prisms arranged about a central axis to form a central channel. The input faces of the prisms are in a common plane which is substantially perpendicular to the central axis. A beam of light which is substantially coaxial to the central axis is incident on the prisms and at least partially strikes a surface area of each prism input face. The incident beam also partially passes through the central channel.
Optical power splitter for splitting high power light
English, R.E. Jr.; Christensen, J.J.
1995-04-18
An optical power splitter for the distribution of high-power light energy has a plurality of prisms arranged about a central axis to form a central channel. The input faces of the prisms are in a common plane which is substantially perpendicular to the central axis. A beam of light which is substantially coaxial to the central axis is incident on the prisms and at least partially strikes a surface area of each prism input face. The incident beam also partially passes through the central channel. 5 figs.
Defect-engineered GaN:Mg nanowire arrays for overall water splitting under violet light
Kibria, M. G.; Chowdhury, F. A.; Zhao, S.; Mi, Z.; Trudeau, M. L.; Guo, H.
2015-03-16
We report that by engineering the intra-gap defect related energy states in GaN nanowire arrays using Mg dopants, efficient and stable overall neutral water splitting can be achieved under violet light. Overall neutral water splitting on Rh/Cr{sub 2}O{sub 3} co-catalyst decorated Mg doped GaN nanowires is demonstrated with intra-gap excitation up to 450 nm. Through optimized Mg doping, the absorbed photon conversion efficiency of GaN nanowires reaches ∼43% at 375–450 nm, providing a viable approach to extend the solar absorption of oxide and non-oxide photocatalysts.
Highly efficient and ultrastable visible-light photocatalytic water splitting over ReS2.
Liu, Huimei; Xu, Bo; Liu, J-M; Yin, Jiang; Miao, Feng; Duan, Chun-Gang; Wan, X G
2016-06-01
Two dimensional materials have many outstanding intrinsic advantages that can be utilized to enhance the photocatalytic efficiency of water splitting. Herein, based on ab initio calculations, we reveal that for monolayer and multilayer rhenium disulphide (ReS2), the band gap and band edge positions are an excellent match with the water splitting energy levels. Moreover, the effective masses of the carriers are relatively light, and the optical absorption coefficients are high under visible illumination. Due to the feature of weak interlayer coupling, these properties are independent of the layer thickness. Our results suggest that ReS2 is a stable and efficient photocatalyst with potential applications in the use of solar energy for water splitting. PMID:27167677
Highly efficient and ultrastable visible-light photocatalytic water splitting over ReS2.
Liu, Huimei; Xu, Bo; Liu, J-M; Yin, Jiang; Miao, Feng; Duan, Chun-Gang; Wan, X G
2016-06-01
Two dimensional materials have many outstanding intrinsic advantages that can be utilized to enhance the photocatalytic efficiency of water splitting. Herein, based on ab initio calculations, we reveal that for monolayer and multilayer rhenium disulphide (ReS2), the band gap and band edge positions are an excellent match with the water splitting energy levels. Moreover, the effective masses of the carriers are relatively light, and the optical absorption coefficients are high under visible illumination. Due to the feature of weak interlayer coupling, these properties are independent of the layer thickness. Our results suggest that ReS2 is a stable and efficient photocatalyst with potential applications in the use of solar energy for water splitting.
Cunefare, David; Cooper, Robert F; Higgins, Brian; Katz, David F; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina
2016-05-01
Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice's coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice's coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images.
Cunefare, David; Cooper, Robert F.; Higgins, Brian; Katz, David F.; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina
2016-01-01
Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice’s coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice’s coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images. PMID:27231641
Stable quantum dot photoelectrolysis cell for unassisted visible light solar water splitting.
Yang, Hong Bin; Miao, Jianwei; Hung, Sung-Fu; Huo, Fengwei; Chen, Hao Ming; Liu, Bin
2014-10-28
Sunlight is an ideal source of energy, and converting sunlight into chemical fuels, mimicking what nature does, has attracted significant attention in the past decade. In terms of solar energy conversion into chemical fuels, solar water splitting for hydrogen production is one of the most attractive renewable energy technologies, and this achievement would satisfy our increasing demand for carbon-neutral sustainable energy. Here, we report corrosion-resistant, nanocomposite photoelectrodes for spontaneous overall solar water splitting, consisting of a CdS quantum dot (QD) modified TiO2 photoanode and a CdSe QD modified NiO photocathode, where cadmium chalcogenide QDs are protected by a ZnS passivation layer and gas evolution cocatalysts. The optimized device exhibited a maximum efficiency of 0.17%, comparable to that of natural photosynthesis with excellent photostability under visible light illumination. Our device shows spontaneous overall water splitting in a nonsacrificial environment under visible light illumination (λ > 400 nm) through mimicking nature's "Z-scheme" process. The results here also provide a conceptual layout to improve the efficiency of solar-to-fuel conversion, which is solely based on facile, scalable solution-phase techniques.
2s Hyperfine splitting in light hydrogen-like atoms: Theory and experiment
Karshenboim, S. G. Kolachevsky, N. N.; Ivanov, V. G.; Fischer, M.; Fendel, P.; Haensch, T. W.
2006-03-15
Since the combination D{sub 21} = 8f{sub HFS}(2s)-f{sub HFS}(1s) of hyperfine intervals in hydrogen and light two-body hydrogen-like atomic systems weakly depends on the nuclear structure, comparison between theory and experiment can be sensitive to high order QED corrections. New theoretical and experimental results are presented. Calculations have been performed for the hydrogen and deuterium atoms and for the helium-3 ion. Experiments on the 2s hyperfine splitting (responsible for the dominant contribution to the error in D{sub 21}) have been conducted for hydrogen and deuterium. The theory and experiment are in good agreement, and their accuracy is comparable to that attained in verifying the QED theory of the hyperfine splitting in leptonic atoms (muonium and positronium)
Coherent and dynamic beam splitting based on light storage in cold atoms
NASA Astrophysics Data System (ADS)
Park, Kwang-Kyoon; Zhao, Tian-Ming; Lee, Jong-Chan; Chough, Young-Tak; Kim, Yoon-Ho
2016-09-01
We demonstrate a coherent and dynamic beam splitter based on light storage in cold atoms. An input weak laser pulse is first stored in a cold atom ensemble via electromagnetically-induced transparency (EIT). A set of counter-propagating control fields, applied at a later time, retrieves the stored pulse into two output spatial modes. The high visibility interference between the two output pulses clearly demonstrates that the beam splitting process is coherent. Furthermore, by manipulating the control lasers, it is possible to dynamically control the storage time, the power splitting ratio, the relative phase, and the optical frequencies of the output pulses. With further improvements, the active beam splitter demonstrated in this work might have applications in photonic photonic quantum information and in all-optical information processing.
Coherent and dynamic beam splitting based on light storage in cold atoms
Park, Kwang-Kyoon; Zhao, Tian-Ming; Lee, Jong-Chan; Chough, Young-Tak; Kim, Yoon-Ho
2016-01-01
We demonstrate a coherent and dynamic beam splitter based on light storage in cold atoms. An input weak laser pulse is first stored in a cold atom ensemble via electromagnetically-induced transparency (EIT). A set of counter-propagating control fields, applied at a later time, retrieves the stored pulse into two output spatial modes. The high visibility interference between the two output pulses clearly demonstrates that the beam splitting process is coherent. Furthermore, by manipulating the control lasers, it is possible to dynamically control the storage time, the power splitting ratio, the relative phase, and the optical frequencies of the output pulses. With further improvements, the active beam splitter demonstrated in this work might have applications in photonic photonic quantum information and in all-optical information processing. PMID:27677457
Dendritic Au/TiO2 nanorod arrays for visible-light driven photoelectrochemical water splitting
NASA Astrophysics Data System (ADS)
Su, Fengli; Wang, Tuo; Lv, Rui; Zhang, Jijie; Zhang, Peng; Lu, Jianwei; Gong, Jinlong
2013-09-01
This paper describes the synthesis of TiO2 branched nanorod arrays (TiO2 BNRs) with plasmonic Au nanoparticles attached on the surface. Such Au/TiO2 BNR composites exhibit high photocatalytic activity in photoelectrochemical (PEC) water splitting. The unique structure of Au/TiO2 BNRs shows enhanced activity with a photocurrent of 0.125 mA cm-2 under visible light (>=420 nm) and 2.32 +/- 0.1 mA cm-2 under AM 1.5 G illumination (100 mW cm-2). The obtained photocurrent is comparable to the highest value ever reported. Furthermore, the Au/TiO2 BNRs achieve the highest efficiency of ~1.27% at a low bias of 0.50 V vs. RHE, indicating elevated charge separation and transportation efficiencies. The high PEC performance is mainly due to the plasmonic effect of Au nanoparticles, which enhances the visible light absorption, together with the large surface area, efficient charge separation and high carrier mobility of the TiO2 BNRs. The carrier density of Au/TiO2 BNRs is nearly 6 times higher than the pristine TiO2 BNRs as calculated by the Mott-Schottky plot. Based on the analysis by UV-Vis spectroscopy, electrochemical impedance spectroscopy, and photoluminescence, a mechanism was proposed to explain the high activity of Au/TiO2 BNRs in PEC water splitting. The capability of synthesizing highly visible light active Au/TiO2 BNR based photocatalysts is useful for solar conversion applications, such as PEC water splitting, dye-sensitized solar cells and photovoltaic devices.This paper describes the synthesis of TiO2 branched nanorod arrays (TiO2 BNRs) with plasmonic Au nanoparticles attached on the surface. Such Au/TiO2 BNR composites exhibit high photocatalytic activity in photoelectrochemical (PEC) water splitting. The unique structure of Au/TiO2 BNRs shows enhanced activity with a photocurrent of 0.125 mA cm-2 under visible light (>=420 nm) and 2.32 +/- 0.1 mA cm-2 under AM 1.5 G illumination (100 mW cm-2). The obtained photocurrent is comparable to the highest value ever
Electric Field-Assisted Photochemical Water Splitting Should Operate with 287 nm Light.
Bachler, Vinzenz; Gärtner, Wolfgang
2016-05-01
The major photoreaction of water is the homolytic splitting of one O-H bond starting from the 1(1) B1 excited state (λmax = 167 nm). This reaction produces H• and •OH radicals. The combination of two H• atoms leads to the potential energy carrier dihydrogen. However, the energy required to obtain the photoreactive 1(1) B1 electronic state is about 7.4 eV, which cannot be effectively provided by solar radiation. The sun light spectrum on earth comprises the visible and ultraviolet region, but shows vanishing intensity near 7 eV (177.1 nm). This work provides theoretical evidence that the photoreactive 1(1) B1 state of water can be shifted into the ultraviolet (UV-B) light region (≈287 nm) by including explicitly an electric field in the calculations of the water absorption spectrum. To accomplish such bathochromic shift, a large field strength of 3.08 VÅ(-1) is required. The field-dependent excitation energies were calculated by applying the symmetry-adapted cluster configuration interaction (SAC-CI) procedure. Based on this theoretical analysis, we propose that photochemical water splitting can be accomplished by means of 287 nm light provided the water molecule is favorably oriented by an external electric field and is subsequently activated by a reversal of the field orientation.
Electric Field-Assisted Photochemical Water Splitting Should Operate with 287 nm Light.
Bachler, Vinzenz; Gärtner, Wolfgang
2016-05-01
The major photoreaction of water is the homolytic splitting of one O-H bond starting from the 1(1) B1 excited state (λmax = 167 nm). This reaction produces H• and •OH radicals. The combination of two H• atoms leads to the potential energy carrier dihydrogen. However, the energy required to obtain the photoreactive 1(1) B1 electronic state is about 7.4 eV, which cannot be effectively provided by solar radiation. The sun light spectrum on earth comprises the visible and ultraviolet region, but shows vanishing intensity near 7 eV (177.1 nm). This work provides theoretical evidence that the photoreactive 1(1) B1 state of water can be shifted into the ultraviolet (UV-B) light region (≈287 nm) by including explicitly an electric field in the calculations of the water absorption spectrum. To accomplish such bathochromic shift, a large field strength of 3.08 VÅ(-1) is required. The field-dependent excitation energies were calculated by applying the symmetry-adapted cluster configuration interaction (SAC-CI) procedure. Based on this theoretical analysis, we propose that photochemical water splitting can be accomplished by means of 287 nm light provided the water molecule is favorably oriented by an external electric field and is subsequently activated by a reversal of the field orientation. PMID:26876336
Software, Anyhere; Fernandes, Luis; Lee, Eleanor; Ward, Greg
2013-03-15
A simulation study was conducted to evaluate lighting energy savings of split-pane electrochromic (EC) windows controlled to satisfy key visual comfort parameters. Using the Radiance lighting simulation software, interior illuminance and luminance levels were computed for a south-facing private office illuminated by a window split into two independently-controlled EC panes. The transmittance of these was optimized hourly for a workplane illuminance target while meeting visual comfort constraints, using a least-squares algorithm with linear inequality constraints. Blinds were successively deployed until visual comfort criteria were satisfied. The energy performance of electrochromics proved to be highly dependent on how blinds were controlled. With hourly blind position adjustments, electrochromics showed significantly higher (62percent and 53percent, respectively without and with overhang) lighting energy consumption than clear glass. With a control algorithm designed to better approximate realistic manual control by an occupant, electrochromics achieved significant savings (48percent and 37percent, respectively without and with overhang). In all cases, energy consumption decreased when the workplace illuminance target was increased. In addition, the fraction of time during which the occupant had an unobstructed view of the outside was significantly greater with electrochromics: 10 months out of the year versus a handful of days for the reference case.
Light-splitting photovoltaic system utilizing two dual-junction solar cells
Xiong, Kanglin; Yang, Hui; Lu, Shulong; Dong, Jianrong; Zhou, Taofei; Wang, Rongxin; Jiang, Desheng
2010-12-15
There are many difficulties limiting the further development of monolithic multi-junction solar cells, such as the growth of lattice-mismatched material and the current matching constraint. As an alternative approach, the light-splitting photovoltaic system is investigated intensively in different aspects, including the energy loss mechanism and the choice of energy bandgaps of solar cells. Based on the investigation, a two-dual junction system has been implemented employing lattice-matched GaInP/GaAs and InGaAsP/InGaAs cells grown epitaxially on GaAs and InP substrates, respectively. (author)
Wang, Jiajun; Meng, Jie; Li, Qunxiang; Yang, Jinlong
2016-06-22
Recently, various single-layer materials have been explored as desirable photocatalyts for water splitting. In this work, based on extensive density functional theory calculations, we examine the geometric, electronic, optical, and potential photocatalytic properties of single-layer cadmium chalcogenides (CdX sheets, X = S, Se, and Te), which are cleaved from the (001) plane of the bulk wurtzite structure. The predicted formation energies have relatively low values and a suitable substrate (i.e. graphene) that can effectively stabilize CdX sheets, which imply that the fabrication and application of CdX sheets are highly possible in experiments. The calculated band gaps, band edge positions and optical absorptions clearly reveal that CdSe and CdTe sheets are promising photocatalysts for water splitting driven by visible light. Moreover, the band gaps and band edge positions of three CdX sheets can be effectively tuned by applying biaxial strain, which then can enhance their photocatalytic performance. These theoretical findings imply that CdX sheets are promising candidates for photocatalytic water splitting. PMID:27296472
Wang, Jiajun; Meng, Jie; Li, Qunxiang; Yang, Jinlong
2016-06-22
Recently, various single-layer materials have been explored as desirable photocatalyts for water splitting. In this work, based on extensive density functional theory calculations, we examine the geometric, electronic, optical, and potential photocatalytic properties of single-layer cadmium chalcogenides (CdX sheets, X = S, Se, and Te), which are cleaved from the (001) plane of the bulk wurtzite structure. The predicted formation energies have relatively low values and a suitable substrate (i.e. graphene) that can effectively stabilize CdX sheets, which imply that the fabrication and application of CdX sheets are highly possible in experiments. The calculated band gaps, band edge positions and optical absorptions clearly reveal that CdSe and CdTe sheets are promising photocatalysts for water splitting driven by visible light. Moreover, the band gaps and band edge positions of three CdX sheets can be effectively tuned by applying biaxial strain, which then can enhance their photocatalytic performance. These theoretical findings imply that CdX sheets are promising candidates for photocatalytic water splitting.
Light induced oxidative water splitting in photosynthesis: energetics, kinetics and mechanism.
Renger, Gernot
2011-01-01
The essential steps of photosynthetic water splitting take place in Photosystem II (PSII) and comprise three different reaction sequences: (i) light induced formation of the radical pair P680(+)Q(A)(-), (ii) P680(+) driven oxidative water splitting into O(2) and four protons, and (iii) two step plastoquinone reduction to plastoquinol by Q(A)(-). This mini-review briefly summarizes our state of knowledge on energetics, kinetics and mechanism of oxidative water splitting. Essential features of the two types of reactions involved are described: (a) P680(+) reduction by the redox active tyrosine Y(z) and (b) sequence of oxidation steps induced by Y(z)(ox) in the water-oxidizing complex (WOC). The rate of the former reaction is limited by the non-adiabatic electron transfer (NET) step and the multi-phase kinetics shown to originate from a sequence of relaxation processes. In marked contrast, the rate of the stepwise oxidation by Y(z)(ox) of the WOC up to the redox level S(3) is not limited by NET but by trigger reactions which probably comprise proton shifts and/or conformational changes. The overall rate of the final reaction sequence leading to formation and release of O(2) is assumed to be limited by the electron transfer step from the S(3) state of WOC to Y(z)(ox) due to involvement of an endergonic redox equilibrium. Currently discussed controversial ideas on possible pathways are briefly outlined. Several crucial points of the mechanism of oxidative water splitting, like O-O bond formation, role of local proton shift(s), details of hydrogen bonding, are still not clarified and remain a challenging topic of future research.
NASA Astrophysics Data System (ADS)
Mateo, Diego; Esteve-Adell, Iván; Albero, Josep; Royo, Juan F. Sánchez; Primo, Ana; Garcia, Hermenegildo
2016-06-01
Development of renewable fuels from solar light appears as one of the main current challenges in energy science. A plethora of photocatalysts have been investigated to obtain hydrogen and oxygen from water and solar light in the last decades. However, the photon-to-hydrogen molecule conversion is still far from allowing real implementation of solar fuels. Here we show that 111 facet-oriented gold nanoplatelets on multilayer graphene films deposited on quartz is a highly active photocatalyst for simulated sunlight overall water splitting into hydrogen and oxygen in the absence of sacrificial electron donors, achieving hydrogen production rate of 1.2 molH2 per gcomposite per h. This photocatalytic activity arises from the gold preferential orientation and the strong gold-graphene interaction occurring in the composite system.
Interface-induced heavy-hole/light-hole splitting of acceptors in silicon
Mol, J. A.; Salfi, J.; Simmons, M. Y.; Rogge, S.; Rahman, R.; Hsueh, Y.; Klimeck, G.; Miwa, J. A.
2015-05-18
The energy spectrum of spin-orbit coupled states of individual sub-surface boron acceptor dopants in silicon have been investigated using scanning tunneling spectroscopy at cryogenic temperatures. The spatially resolved tunnel spectra show two resonances, which we ascribe to the heavy- and light-hole Kramers doublets. This type of broken degeneracy has recently been argued to be advantageous for the lifetime of acceptor-based qubits [R. Ruskov and C. Tahan, Phys. Rev. B 88, 064308 (2013)]. The depth dependent energy splitting between the heavy- and light-hole Kramers doublets is consistent with tight binding calculations, and is in excess of 1 meV for all acceptors within the experimentally accessible depth range (<2 nm from the surface). These results will aid the development of tunable acceptor-based qubits in silicon with long coherence times and the possibility for electrical manipulation.
Mateo, Diego; Esteve-Adell, Iván; Albero, Josep; Royo, Juan F. Sánchez; Primo, Ana; Garcia, Hermenegildo
2016-01-01
Development of renewable fuels from solar light appears as one of the main current challenges in energy science. A plethora of photocatalysts have been investigated to obtain hydrogen and oxygen from water and solar light in the last decades. However, the photon-to-hydrogen molecule conversion is still far from allowing real implementation of solar fuels. Here we show that 111 facet-oriented gold nanoplatelets on multilayer graphene films deposited on quartz is a highly active photocatalyst for simulated sunlight overall water splitting into hydrogen and oxygen in the absence of sacrificial electron donors, achieving hydrogen production rate of 1.2 molH2 per gcomposite per h. This photocatalytic activity arises from the gold preferential orientation and the strong gold–graphene interaction occurring in the composite system. PMID:27264495
Mateo, Diego; Esteve-Adell, Iván; Albero, Josep; Royo, Juan F Sánchez; Primo, Ana; Garcia, Hermenegildo
2016-01-01
Development of renewable fuels from solar light appears as one of the main current challenges in energy science. A plethora of photocatalysts have been investigated to obtain hydrogen and oxygen from water and solar light in the last decades. However, the photon-to-hydrogen molecule conversion is still far from allowing real implementation of solar fuels. Here we show that 111 facet-oriented gold nanoplatelets on multilayer graphene films deposited on quartz is a highly active photocatalyst for simulated sunlight overall water splitting into hydrogen and oxygen in the absence of sacrificial electron donors, achieving hydrogen production rate of 1.2 molH2 per gcomposite per h. This photocatalytic activity arises from the gold preferential orientation and the strong gold-graphene interaction occurring in the composite system. PMID:27264495
Generating and Separating Twisted Light by gradient-rotation Split-Ring Antenna Metasurfaces.
Zeng, Jinwei; Li, Ling; Yang, Xiaodong; Gao, Jie
2016-05-11
Nanoscale compact optical vortex generators promise substantially significant prospects in modern optics and photonics, leading to many advances in sensing, imaging, quantum communication, and optical manipulation. However, conventional vortex generators often suffer from bulky size, low vortex mode purity in the converted beam, or limited operation bandwidth. Here, we design and demonstrate gradient-rotation split-ring antenna metasurfaces as unique spin-to-orbital angular momentum beam converters to simultaneously generate and separate pure optical vortices in a broad wavelength range. Our proposed design has the potential for realizing miniaturized on-chip OAM-multiplexers, as well as enabling new types of metasurface devices for the manipulation of complex structured light beams. PMID:27092965
Waszczak, Adam; Chang, Chan-Kao; Cheng, Yu-Chi; Ip, Wing-Huen; Kinoshita, Daisuke; Ofek, Eran O.; Laher, Russ; Surace, Jason; Masci, Frank; Helou, George; Levitan, David; Prince, Thomas A.; Kulkarni, Shrinivas
2015-09-15
We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ∼53,000 fitted periods. By this method we find that 9033 of our light curves (of ∼8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ∼2 g cm{sup −3}, while C types have a lower limit of between 1 and 2 g cm{sup −3}. These results are in agreement with previous density estimates. For 5–20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms
NASA Astrophysics Data System (ADS)
Waszczak, Adam; Chang, Chan-Kao; Ofek, Eran O.; Laher, Russ; Masci, Frank; Levitan, David; Surace, Jason; Cheng, Yu-Chi; Ip, Wing-Huen; Kinoshita, Daisuke; Helou, George; Prince, Thomas A.; Kulkarni, Shrinivas
2015-09-01
We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ˜53,000 fitted periods. By this method we find that 9033 of our light curves (of ˜8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ˜2 g cm-3, while C types have a lower limit of between 1 and 2 g cm-3. These results are in agreement with previous density estimates. For 5-20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms scatter by a factor of
NASA Astrophysics Data System (ADS)
Waszczak, Adam; Chang, Chan-Kao; Ofek, Eran O.; Laher, Russ; Masci, Frank; Levitan, David; Surace, Jason; Cheng, Yu-Chi; Ip, Wing-Huen; Kinoshita, Daisuke; Helou, George; Prince, Thomas A.; Kulkarni, Shrinivas
2015-09-01
We fit 54,296 sparsely sampled asteroid light curves in the Palomar Transient Factory survey to a combined rotation plus phase-function model. Each light curve consists of 20 or more observations acquired in a single opposition. Using 805 asteroids in our sample that have reference periods in the literature, we find that the reliability of our fitted periods is a complicated function of the period, amplitude, apparent magnitude, and other light-curve attributes. Using the 805-asteroid ground-truth sample, we train an automated classifier to estimate (along with manual inspection) the validity of the remaining ∼53,000 fitted periods. By this method we find that 9033 of our light curves (of ∼8300 unique asteroids) have “reliable” periods. Subsequent consideration of asteroids with multiple light-curve fits indicates a 4% contamination in these “reliable” periods. For 3902 light curves with sufficient phase-angle coverage and either a reliable fit period or low amplitude, we examine the distribution of several phase-function parameters, none of which are bimodal though all correlate with the bond albedo and with visible-band colors. Comparing the theoretical maximal spin rate of a fluid body with our amplitude versus spin-rate distribution suggests that, if held together only by self-gravity, most asteroids are in general less dense than ∼2 g cm‑3, while C types have a lower limit of between 1 and 2 g cm‑3. These results are in agreement with previous density estimates. For 5–20 km diameters, S types rotate faster and have lower amplitudes than C types. If both populations share the same angular momentum, this may indicate the two types’ differing ability to deform under rotational stress. Lastly, we compare our absolute magnitudes (and apparent-magnitude residuals) to those of the Minor Planet Center’s nominal (G = 0.15, rotation-neglecting) model; our phase-function plus Fourier-series fitting reduces asteroid photometric rms scatter by a
Petrov, P. V.; Ivanov, Yu. L.
2013-04-15
The paramagnetic splitting of a light-hole level in a GaAs/AlGaAs quantum well is experimentally measured by the method of measuring the polarized photoluminescence in the magnetic field. The phenomenon of giant splitting, which was previously predicted theoretically and leads to an increase in the g factor of a light hole to 9.4, is found.
MWCNT/WO{sub 3} nanocomposite photoanode for visible light induced water splitting
Yousefzadeh, Samira; Reyhani, Ali; Naseri, Naimeh; Moshfegh, Alireza Z.
2013-08-15
The Multi-walled carbon nanotube (MWCNT)/WO{sub 3} nanocomposite thin films with different MWCNT’s weight percentages were prepared by sol–gel method as visible light induced photoanode in water splitting reaction. Weight percentage of MWCNT in the all nanocomposite thin films was confirmed by TGA/DSC analysis. According to XPS analysis, oxygenated groups at the surface of the MWCNT and stoichiometric formation of WO{sub 3} thin films were determined, while the crystalline structure of the nanocomposite samples was studied by XRD indicating (0 0 2) peak of MWCNT in the monoclinic phase of WO{sub 3}. The influence of different weight percentage (wt%) of MWCNT on WO{sub 3} photoactivity showed that the electron conductivity, charge transfer and electron life time had improved as compared with the pure WO{sub 3}. Based on linear sweep voltammetry and chronoamperometry measurements, the (1 wt%) MWCNT/WO{sub 3} nanocomposite thin films photoanode has a maximum photocurrent density of ∼4.5 A/m{sup 2} and electron life time of about 57 s. - Graphical abstract: Photocurrent density versus time at constant potential (0.7 V) for the WO{sub 3} films containing different MWCNT weight percentages annealed at 400 °C under 1000 Wm{sup −2} visible photo-illumination. Display Omitted - Highlights: • MWCNT/ WO{sub 3} nanocomposite thin films were synthesized using sol–gel derived method. • TGA/DSC confirmed the weight percentage of MWCNT in the all nanocomposite thin films. • XPS analysis revealed that WO{sub 3} was attached on the oxygenated group of MWCNT surface. • The Highest Photoelectrochemical activity is achieved for (1 wt%)MWCNT/WO{sub 3} thin film.
Zhang, Jianfa; Liu, Wei; Zhu, Zhihong; Yuan, Xiaodong; Qin, Shiqiao
2014-12-15
Strong subwavelength field enhancement has often been assumed to be unique to plasmonic nanostructures. Here we propose a type of all-dielectric metamaterials based on split bar resonators. The nano gap at the centre of the resonant elements results in large local field enhancement and light localization in the surrounding medium, which can be employed for strong light-matter interactions. In a Fano-resonant dielectric metamaterial comprising pairs of asymmetric split silicon bars, the enhancement of electric field amplitude in the gap exceeds 120 while the averaged electromagnetic energy density is enhanced by more than 7000 times. An optical refractive index sensor with a potential sensitivity of 525 nm/RIU is designed based on the proposed metamaterials. The proposed concept can be applied to other types of dielectric nanostructures and may stimulate further research of dielectric metamaterials for applications ranging from nonlinear optics and sensing to the realization of new types of active lasing devices.
Non-destructive splitter of twisted light based on modes splitting in a ring cavity.
Li, Yan; Zhou, Zhi-Yuan; Ding, Dong-Sheng; Zhang, Wei; Shi, Shuai; Shi, Bao-Sen; Guo, Guang-Can
2016-02-01
Efficiently discriminating beams carrying different orbital angular momentum (OAM) is of fundamental importance for various applications including high capacity optical communication and quantum information processing. We design and experimentally verify a distinguished method for effectively splitting different OAM-carried beams by introducing Dove prisms in a ring cavity. Because of rotational symmetry broken of two OAM-carried beams with opposite topological charges, their transmission spectra will split. When mode and impedance matches between the cavity and one OAM-carried beam are achieved, this beam will transmit through the cavity and other beam will be reflected, both beams keep their spatial shapes. In this case, the cavity acts like a polarized beam splitter. Besides, the transmitting beam can be selected at your will, the splitting efficiency can reach unity if the cavity is lossless and it completely matches the beam. Furthermore, beams carry multi-OAMs can also be split by cascading ring cavities. PMID:26906792
Light sources generating self-splitting beams and their propagation in non-Kolmogorov turbulence.
Mei, Zhangrong
2014-06-01
A class of random sources producing far fields self-splitting intensity profiles with variable spacing between the x and y directions is introduced. The beam conditions for ensuring the sources to generate a beam are derived. Based on the derived analytical expression, the evolution behavior of the beams produced by these families of sources in free space and turbulence atmospheric are explored and comparatively analyzed. By changing the modulation parameters n and m, the degree of coherence of Gaussian Schell-model source in the x and y directions are modulated respectively, and then the number of splitting beams and the spacing between splitting beams can be adjusted. It is illustrated that the self-splitting intensity profile is stable when beams propagate in free space, but they eventually transformed into a Gaussian profiles when it passes at sufficiently large distances from its source through the turbulent atmosphere.
Yeh, Te-Fu; Teng, Chiao-Yi; Chen, Shean-Jen; Teng, Hsisheng
2014-05-28
Nitrogen-doped graphene oxide quantum dots exhibit both p- and n-type conductivities and catalyze overall water-splitting under visible-light irradiation. The quantum dots contain p-n type photochemical diodes, in which the carbon sp(2) clusters serve as the interfacial junction. The active sites for H2 and O2 evolution are the p- and n-domains, respectively, and the reaction mimics biological photosynthesis.
Plasmonic enhancement of visible-light water splitting with Au-TiO2 composite aerogels.
DeSario, Paul A; Pietron, Jeremy J; DeVantier, Devyn E; Brintlinger, Todd H; Stroud, Rhonda M; Rolison, Debra R
2013-09-01
We demonstrate plasmonic enhancement of visible-light-driven splitting of water at three-dimensionally (3D) networked gold-titania (Au-TiO2) aerogels. The sol-gel-derived ultraporous composite nanoarchitecture, which contains 1 to 8.5 wt% Au nanoparticles and titania in the anatase form, retains the high surface area and mesoporosity of unmodified TiO2 aerogels and maintains stable dispersion of the ~5 nm Au guests. A broad surface plasmon resonance (SPR) feature centered at ~550 nm is present for the Au-TiO2 aerogels, but not Au-free TiO2 aerogels, and spans a wide range of the visible spectrum. Gold-derived SPR in Au-TiO2 aerogels cast as films on transparent electrodes drives photoelectrochemical oxidation of aqueous hydroxide and extends the photocatalytic activity of TiO2 from the ultraviolet region to visible wavelengths exceeding 700 nm. Films of Au-TiO2 aerogels in which Au nanoparticles are deposited on pre-formed TiO2 aerogels by a deposition-precipitation method (DP Au/TiO2) also photoelectrochemically oxidize aqueous hydroxide, but less efficiently than 3D Au-TiO2, despite having an essentially identical Au nanoparticle weight fraction and size distribution. For example, 3D Au-TiO2 containing 1 wt% Au is as active as DP Au/TiO2 with 4 wt% Au. The higher photocatalytic activity of 3D Au-TiO2 derives only in part from its ability to retain the surface area and porosity of unmodified TiO2 aerogel. The magnitude of improvement indicates that in the 3D arrangement either a more accessible photoelectrochemical reaction interphase (three-phase boundary) exists or more efficient conversion of excited surface plasmons into charge carriers occurs, thereby amplifying reactivity over DP Au/TiO2. The difference in photocatalytic efficiency between the two forms of Au-TiO2 demonstrates the importance of defining the structure of Au[parallel]TiO2 interfaces within catalytic Au-TiO2 nanoarchitectures. PMID:23877169
NASA Astrophysics Data System (ADS)
Wu, Z. W.; Volotka, A. V.; Surzhykov, A.; Dong, C. Z.; Fritzsche, S.
2016-06-01
The angular distribution and linear polarization of the fluorescence light following the resonant photoexcitation is investigated within the framework of density matrix and second-order perturbation theory. Emphasis has been placed on "signatures" for determining the level sequence and splitting of intermediate (partially) overlapping resonances, if analyzed as a function of photon energy of incident light. Detailed computations within the multiconfiguration Dirac-Fock method have been performed, especially for the 1 s22 s22 p63 s ,Ji=1 /2 +γ1→(1s22 s 2 p63 s ) 13 p3 /2,J =1 /2 ,3 /2 →1 s22 s22 p63 s ,Jf=1 /2 +γ2 photoexcitation and subsequent fluorescence emission of atomic sodium. A remarkably strong dependence of the angular distribution and linear polarization of the γ2 fluorescence emission is found upon the level sequence and splitting of the intermediate (1s22 s 2 p63 s ) 13 p3 /2,J =1 /2 ,3 /2 overlapping resonances owing to their finite lifetime (linewidth). We therefore suggest that accurate measurements of the angular distribution and linear polarization might help identify the sequence and small splittings of closely spaced energy levels, even if they cannot be spectroscopically resolved.
From a Philanthropic Idea to Building of Civic Hospital in Split in Light of New Archival Evidence
Brisky, Livia; Fatović-Ferenčić, Stella
2006-01-01
We investigated the circumstances of building of the Civic Hospital in Split in the light of new archival evidence. The study necessitated a thorough review of the older historiography and previously unpublished archival sources kept in the State Archives in Venice and Zadar. The findings showed that construction of the hospital building finished in 1797, ie, five years later than officially cited. The topographical plan and the original project of the Split Civic Hospital were found, as well as the name of the project's author and the building supervisor. The data on the earliest efforts of Ergovac brothers to acquire land and building permission were corrected. The study revealed a recognizable pattern in the attitude of the authorities toward the establishment of a hospital at the end of 18th century. PMID:16489710
Jia, Qingxin; Iwashina, Katsuya; Kudo, Akihiko
2012-01-01
An efficient BiVO4 thin film electrode for overall water splitting was prepared by dipping an F-doped SnO2 (FTO) substrate electrode in an aqueous nitric acid solution of Bi(NO3)3 and NH4VO3, and subsequently calcining it. X-ray diffraction of the BiVO4 thin film revealed that a photocatalytically active phase of scheelite-monoclinic BiVO4 was obtained. Scanning electron microscopy images showed that the surface of an FTO substrate was uniformly coated with the BiVO4 film with 300–400 nm of the thickness. The BiVO4 thin film electrode gave an excellent anodic photocurrent with 73% of an IPCE at 420 nm at 1.0 V vs. Ag/AgCl. Modification with CoO on the BiVO4 electrode improved the photoelectrochemical property. A photoelectrochemical cell consisting of the BiVO4 thin film electrode with and without CoO, and a Pt counter electrode was constructed for water splitting under visible light irradiation and simulated sunlight irradiation. Photocurrent due to water splitting to form H2 and O2 was confirmed with applying an external bias smaller than 1.23 V that is a theoretical voltage for electrolysis of water. Water splitting without applying external bias under visible light irradiation was demonstrated using a SrTiO3∶Rh photocathode and the BiVO4 photoanode. PMID:22699499
GASOLINE/DIESEL PM SPLIT STUDY: LIGHT-DUTY VEHICLE TESTING, DATA, AND ANALYSIS
During June 2001, the EPA participated in DOE's Gasoline/Diesel PM Split Study in Riverside, California. The purpose of the study was to determine the contribution of diesel versus gasoline-powered exhaust to the particulate matter (PM) inventory in the South Coast Air Basin. T...
In the present investigation, hydrogen production via water splitting by nano ferrites has been studied using ethanol as the sacrificial donor. The nano ferrite has shown great potential in hydrogen generation with hydrogen yield of 8275 9moles/h/ g of photocatalyst under visible...
Tsuji, Kohei; Tomita, Osamu; Higashi, Masanobu; Abe, Ryu
2016-08-23
In the present study, a polyoxometalate is for the first time applied as a shuttle redox in two-step (Z-Scheme) photocatalytic water splitting. Photocatalytic H2 evolution using a Mn-substituted polyoxometalate [SiW11 O39 Mn(II) (H2 O)](6-) as an electron donor proceeded over a Ru-loaded SrTiO3 :Rh photocatalyst under visible light with relatively high selectivity, accompanied by the stoichiometric production of its oxidized form [SiW11 O39 Mn(III) (H2 O)](5-) . Photocatalytic O2 evolution using the oxidized [SiW11 O39 Mn(III) (H2 O)](5-) as an electron acceptor proceeded over PtOx -loaded WO3 photocatalyst under visible light with relatively high quantum efficiency and selectivity, whereas the loading of effective PtOx cocatalyst was necessary to facilitate the reduction of polyoxometalate. Finally, a two-step water splitting into H2 and O2 was demonstrated under visible light using the couple of Mn-substituted polyoxometalate as shuttle redox between Ru/SrTiO3 :Rh and PtOx /WO3 photocatalysts, under mildly acidic conditions with pH≈4.5.
NASA Astrophysics Data System (ADS)
Dillert, Ralf; Taffa, Dereje H.; Wark, Michael; Bredow, Thomas; Bahnemann, Detlef W.
2015-10-01
The utilization of solar light for the photoelectrochemical and photocatalytic production of molecular hydrogen from water is a scientific and technical challenge. Semiconductors with suitable properties to promote solar-driven water splitting are a desideratum. A hitherto rarely investigated group of semiconductors are ferrites with the empirical formula MFe2O4 and related compounds. This contribution summarizes the published results of the experimental investigations on the photoelectrochemical and photocatalytic properties of these compounds. It will be shown that the potential of this group of compounds in regard to the production of solar hydrogen has not been fully explored yet.
Solar-Light-Driven Pure Water Splitting with Ultrathin BiOCl Nanosheets.
Zhang, Ling; Han, Zhongkang; Wang, Wenzhong; Li, Xiaoman; Su, Yang; Jiang, Dong; Lei, Xiaoling; Sun, Songmei
2015-12-01
A suitable photocatalyst for overall water splitting has been produced by overcoming the disadvantage of the band structure in bulk BiOCl by reducing the thickness to the quantum scale. The ultrathin BiOCl nanosheets with surface/subsurface defects realized the solar-driven pure water splitting in the absence of any co-catalysts or sacrificial agent. These surface defects cannot only shift both the valence band and conduction band upwards for band-gap narrowing but also promote charge-carrier separation. The amount of defects in the outer layer surface of BiOCl results in an enhancement of carrier density and faster charge transport. First-principles calculations provide clear evidence that the formation of surface oxygen vacancies is easier for the ultrathin BiOCl nanosheets than for its thicker counterpart. These defects can serve as active sites to effectively adsorb and dissociate H2 O molecules, resulting in a significantly improved water-splitting performance.
Arrays of templated TiO2 nanofibres as improved photoanodes for water splitting under visible light
NASA Astrophysics Data System (ADS)
Ongaro, M.; Mardegan, A.; Stortini, A. M.; Signoretto, M.; Ugo, P.
2015-04-01
Arrays of TiO2 nanofibres (NFs) were successfully prepared by template sol-gel synthesis, using track-etched polycarbonate membranes as structure directing agent. The control of the sol-gel kinetic was crucial in order to homogeneously fill the pores with a continuous framework. For this reason acetylacetone was added to the sol-gel mixture as chelating agent. The band edge positions of TiO2 NFs were determined by a Mott-Schottky plot and diffuse reflectance analysis. The results support the presence of trace dopants which can act favorably with respect to the photoelectrochemical properties. The TiO2 NFs array showed enhanced photoelectrochemical activity both under UV light and visible light when used as photoanodes for the water splitting reaction.
Azzam, R M A
2015-12-01
Conditions for achieving equal and opposite angular deflections of a light beam by reflection and refraction at an air-dielectric boundary are determined. Such angularly symmetric beam splitting (ASBS) is possible only if the angle of incidence is >60° by exactly one third of the angle of refraction. This simple law, plus Snell's law, leads to several analytical results that clarify all aspects of this phenomenon. In particular, it is shown that the intensities of the two symmetrically deflected beams can be equalized by proper choice of the prism refractive index and the azimuth of incident linearly polarized light. ASBS enables a geometrically attractive layout of optical systems that employ multiple prism beam splitters.
Johnson, Steve A.
1990-01-01
An arrangement especially suitable for use in a laser apparatus for converting a plurality of different input light beams, for example copper vapor laser beams, into a plurality of substantially identical light beams is disclosed herein. This arrangement utilizes an optical mixing bar which is preferably integrally formed as a single unit and which includes a main body for mixing light therein, a flat input surface on one end of the main body, and a multi-faceted output face on the opposite end of the main body. This arrangement also includes means for directing the plurality of different input light beams onto the input face of the mixing base, whereby to cause the different beams to mix within the main body of the mixing bar and exit the latter from its multi-faceted output face as the desired plurality of substantially identical output beams.
Wu, Yun-Ben; Yang, Wen; Wang, Tong-Biao; Deng, Xin-Hua; Liu, Jiang-Tao
2016-01-01
The light absorption of a monolayer graphene-molybdenum disulfide photovoltaic (GM-PV) cell in a wedge-shaped microcavity with a spectrum-splitting structure is investigated theoretically. The GM-PV cell, which is three times thinner than the traditional photovoltaic cell, exhibits up to 98% light absorptance in a wide wavelength range. This rate exceeds the fundamental limit of nanophotonic light trapping in solar cells. The effects of defect layer thickness, GM-PV cell position in the microcavity, incident angle, and lens aberration on the light absorptance of the GM-PV cell are explored. Despite these effects, the GM-PV cell can still achieve at least 90% light absorptance with the current technology. Our proposal provides different methods to design light-trapping structures and apply spectrum-splitting systems. PMID:26864749
Wu, Yun-Ben; Yang, Wen; Wang, Tong-Biao; Deng, Xin-Hua; Liu, Jiang-Tao
2016-01-01
The light absorption of a monolayer graphene-molybdenum disulfide photovoltaic (GM-PV) cell in a wedge-shaped microcavity with a spectrum-splitting structure is investigated theoretically. The GM-PV cell, which is three times thinner than the traditional photovoltaic cell, exhibits up to 98% light absorptance in a wide wavelength range. This rate exceeds the fundamental limit of nanophotonic light trapping in solar cells. The effects of defect layer thickness, GM-PV cell position in the microcavity, incident angle, and lens aberration on the light absorptance of the GM-PV cell are explored. Despite these effects, the GM-PV cell can still achieve at least 90% light absorptance with the current technology. Our proposal provides different methods to design light-trapping structures and apply spectrum-splitting systems. PMID:26864749
NASA Astrophysics Data System (ADS)
Wu, Yun-Ben; Yang, Wen; Wang, Tong-Biao; Deng, Xin-Hua; Liu, Jiang-Tao
2016-02-01
The light absorption of a monolayer graphene-molybdenum disulfide photovoltaic (GM-PV) cell in a wedge-shaped microcavity with a spectrum-splitting structure is investigated theoretically. The GM-PV cell, which is three times thinner than the traditional photovoltaic cell, exhibits up to 98% light absorptance in a wide wavelength range. This rate exceeds the fundamental limit of nanophotonic light trapping in solar cells. The effects of defect layer thickness, GM-PV cell position in the microcavity, incident angle, and lens aberration on the light absorptance of the GM-PV cell are explored. Despite these effects, the GM-PV cell can still achieve at least 90% light absorptance with the current technology. Our proposal provides different methods to design light-trapping structures and apply spectrum-splitting systems.
Wu, Yun-Ben; Yang, Wen; Wang, Tong-Biao; Deng, Xin-Hua; Liu, Jiang-Tao
2016-02-11
The light absorption of a monolayer graphene-molybdenum disulfide photovoltaic (GM-PV) cell in a wedge-shaped microcavity with a spectrum-splitting structure is investigated theoretically. The GM-PV cell, which is three times thinner than the traditional photovoltaic cell, exhibits up to 98% light absorptance in a wide wavelength range. This rate exceeds the fundamental limit of nanophotonic light trapping in solar cells. The effects of defect layer thickness, GM-PV cell position in the microcavity, incident angle, and lens aberration on the light absorptance of the GM-PV cell are explored. Despite these effects, the GM-PV cell can still achieve at least 90% light absorptance with the current technology. Our proposal provides different methods to design light-trapping structures and apply spectrum-splitting systems.
Light Makes a Surface Banana-Bond Split: Photodesorption of Molecular Hydrogen from RuO2(110).
Henderson, Michael A; Mu, Rentao; Dahal, Arjun; Lyubinetsky, Igor; Dohnálek, Zdenek; Glezakou, Vassiliki-Alexandra; Rousseau, Roger
2016-07-20
The coordination of H2 to a metal center via polarization of its σ bond electron density, known as a Kubas complex, is the means by which H2 chemisorbs at Ru(4+) sites on the rutile RuO2(110) surface. This distortion of electron density off an interatomic axis is often described as a 'banana-bond.' We show that the Ru-H2 banana-bond can be destabilized and split using visible light. Photodesorption of H2 (or D2) is evident by mass spectrometry and scanning tunneling microscopy. From time-dependent density functional theory, the key optical excitation splitting the Ru-H2 complex involves an interband transition in RuO2 which effectively diminishes its Lewis acidity, thereby weakening the Kubas complex. Such excitations are not expected to affect adsorbates on RuO2 given its metallic properties. Therefore, this common thermal cocatalyst employed in photocatalysis is, itself, photoactive. PMID:27390889
Phase transition-induced band edge engineering of BiVO4 to split pure water under visible light
Jo, Won Jun; Kang, Hyun Joon; Kong, Ki-Jeong; Lee, Yun Seog; Park, Hunmin; Lee, Younghye; Buonassisi, Tonio; Gleason, Karen K.; Lee, Jae Sung
2015-01-01
Through phase transition-induced band edge engineering by dual doping with In and Mo, a new greenish BiVO4 (Bi1-XInXV1-XMoXO4) is developed that has a larger band gap energy than the usual yellow scheelite monoclinic BiVO4 as well as a higher (more negative) conduction band than H+/H2 potential [0 VRHE (reversible hydrogen electrode) at pH 7]. Hence, it can extract H2 from pure water by visible light-driven overall water splitting without using any sacrificial reagents. The density functional theory calculation indicates that In3+/Mo6+ dual doping triggers partial phase transformation from pure monoclinic BiVO4 to a mixture of monoclinic BiVO4 and tetragonal BiVO4, which sequentially leads to unit cell volume growth, compressive lattice strain increase, conduction band edge uplift, and band gap widening. PMID:26508636
Pan, Hui; Qiu, Xiaofeng; Ivanov, Ilia N; Meyer III, Harry M; Wang, Wei; Zhu, Wenguang; Paranthaman, Mariappan Parans; Zhang, Zhenyu; Eres, Gyula; Gu, Baohua
2009-01-01
We report that mild oxidation of Ti foils in air results in brookite-rich titanium oxide (TiO2) films with similar spectral response to that of dye-sensitized TiO2. X-ray powder diffraction and Raman spectroscopy show that the onset of brookite formation occurs at 500 8C, and the material is characterized by a strong absorption band in the visible spectral range. The first-principle calculations show that enhanced visible light absorption correlates with the presence of Ti interstitials. Photocurrent density measurements of water splitting reveal that the brookite-rich TiO2 exhibits the highest photocatalytic performance among the different forms of TiO2 produced by oxidation of Ti foils. With increasing oxidation temperature transformation to the rutile phase accompanied by declining visible range photoactivity is observed.
Kravets, V G; Grigorenko, A N
2015-11-30
Water splitting is unanimously recognized as environment friendly, potentially low cost and renewable energy solution based on the future hydrogen economy. Especially appealing is photocatalytic water splitting whereby a suitably chosen catalyst dramatically improves efficiency of the hydrogen production driven by direct sunlight and allows it to happen even at zero driving potential. Here, we suggest a new class of stable photocatalysts and the corresponding principle for catalytic water splitting in which infrared and visible light play the main role in producing the photocurrent and hydrogen. The new class of catalysts - ionic or covalent binary metals with layered graphite-like structures - effectively absorb visible and infrared light facilitating the reaction of water splitting, suppress the inverse reaction of ion recombination by separating ions due to internal electric fields existing near alternating layers, provide the sites for ion trapping of both polarities, and finally deliver the electrons and holes required to generate hydrogen and oxygen gases. As an example, we demonstrate conversion efficiency of ~27% at bias voltage V_{bias} = 0.5V for magnesium diboride working as a catalyst for photoinduced water splitting. We discuss its advantages over some existing materials and propose the underlying mechanism of photocatalytic water splitting by binary layered metals.
Kravets, V G; Grigorenko, A N
2015-11-30
Water splitting is unanimously recognized as environment friendly, potentially low cost and renewable energy solution based on the future hydrogen economy. Especially appealing is photocatalytic water splitting whereby a suitably chosen catalyst dramatically improves efficiency of the hydrogen production driven by direct sunlight and allows it to happen even at zero driving potential. Here, we suggest a new class of stable photocatalysts and the corresponding principle for catalytic water splitting in which infrared and visible light play the main role in producing the photocurrent and hydrogen. The new class of catalysts - ionic or covalent binary metals with layered graphite-like structures - effectively absorb visible and infrared light facilitating the reaction of water splitting, suppress the inverse reaction of ion recombination by separating ions due to internal electric fields existing near alternating layers, provide the sites for ion trapping of both polarities, and finally deliver the electrons and holes required to generate hydrogen and oxygen gases. As an example, we demonstrate conversion efficiency of ~27% at bias voltage V_{bias} = 0.5V for magnesium diboride working as a catalyst for photoinduced water splitting. We discuss its advantages over some existing materials and propose the underlying mechanism of photocatalytic water splitting by binary layered metals. PMID:26698811
Light to Electrons to Bonds: Imaging Water Splitting and Collecting Photoexcited Electrons
NASA Astrophysics Data System (ADS)
Leenheer, Andrew Jay
Photoelectrochemical devices can store solar energy as chemical bonds in fuels, but more control over the materials involved is needed for economic feasibility. Both efficient capture of photon energy into electron energy and subsequent electron transfer and bond formation are necessary, and this thesis explores various steps of the process. To look at the electrochemical fuel formation step, the spatially-resolved reaction rate on a water-splitting electrode was imaged during operation at a few-micron scale using optical microscopy. One method involved localized excitation of a semiconductor photoanode and recording the growth rate of bubbles to determine the local reaction rate. A second method imaged the reactant profile with a pH-sensitive fluorophore in the electrolyte to determine the local three-dimensional pH profile at patterned electrocatalysts in a confocal microscope. These methods provide insight on surface features optimal for efficient electron transfer into fuel products. A second set of studies examined the initial process of photoexcited electron transport and collection. An independent method to measure the minority carrier diffusion length in semiconductor photoelectrodes was developed, in which a wedge geometry is back illuminated with a small scanned spot. The diffusion length can be determined from the exponential decrease of photocurrent with thickness, and the method was demonstrated on solid-state silicon wedge diodes, as well as tungsten oxide thin-film wedge photoanodes. Finally, the possibility of absorbing and collecting sub-bandgap illumination via plasmon-enhanced hot carrier internal photoemission was modeled to predict the energy conversion efficiency. The effect of photon polarization on emission yield was experimentally tested using gold nanoantennas buried in silicon, and the correlation was found to be small.
Cheung, K.; Chiang, C.-W.
2005-05-01
In split supersymmetry, the supersymmetric scalar particles are all very heavy, at least at the order of 10{sup 9} GeV, but the gauginos, Higgsinos, and one of the neutral Higgs bosons remain below a TeV. Here we further split the split supersymmetry by taking the Higgsino mass parameter {mu} to be very large. In this case, the {mu} problem is avoided and we keep the wino as a dark matter candidate. A crude gauge-coupling unification is still preserved. Dark matter signals and collider phenomenology are discussed in this {mu}-split SUSY scenario. The most interesting dark matter signal is the annihilation into monochromatic photons. In colliders, chargino-pair and the associated chargino-neutralino production cross sections have a certain ratio due to gauge couplings.
NASA Astrophysics Data System (ADS)
Sambandam, Balaji; Michael, Robin Jude Vimal; Manoharan, Periakaruppan T.
2015-08-01
ZnO nanorods and Mn/ZnO microflowers with nano-sized petals exhibit singly ionized oxygen vacancies, V+O. This is strongly supported by a green photoluminescence emission at 2.22 eV and an EPR g value of 1.953, both of which are suppressed greatly after annealing in an oxygen atmosphere. A strong red emission observed during exposure to X-rays reveals the presence of F+ centres as a consequence of the V+O. Mn/ZnO displayed enhanced H2 generation with visible light exposure, when compared to pure ZnO and annealed Mn/ZnO in the visible region, which directly correlated with the oxygen vacancy concentration. There is an interesting correlation between the intensities of the EPR lines at the g-value of 1.953 due to the oxygen vacancies, the intensity of light emitted from the exposure to X-rays, the intensity of the photoluminescence due to oxygen vacancies and the quantity of H2 produced by the photocatalytic effect when comparing the three different nanomaterials, viz. pure ZnO, Mn/ZnO before and after annealing, all having been made exactly by the same methodologies.ZnO nanorods and Mn/ZnO microflowers with nano-sized petals exhibit singly ionized oxygen vacancies, V+O. This is strongly supported by a green photoluminescence emission at 2.22 eV and an EPR g value of 1.953, both of which are suppressed greatly after annealing in an oxygen atmosphere. A strong red emission observed during exposure to X-rays reveals the presence of F+ centres as a consequence of the V+O. Mn/ZnO displayed enhanced H2 generation with visible light exposure, when compared to pure ZnO and annealed Mn/ZnO in the visible region, which directly correlated with the oxygen vacancy concentration. There is an interesting correlation between the intensities of the EPR lines at the g-value of 1.953 due to the oxygen vacancies, the intensity of light emitted from the exposure to X-rays, the intensity of the photoluminescence due to oxygen vacancies and the quantity of H2 produced by the
Light trap with reactive sun tracking for high-efficiency spectrum splitting photovoltaic conversion
NASA Astrophysics Data System (ADS)
Apostoleris, H.; Chiesa, M.; Stefancich, M.
2015-05-01
We present a design for a modification of a previously proposed light-trapping solar collector that enables reactive solar tracking by the incorporation of an optically activated transparency-switching material. The material forms an entry aperture whose position reactively varies to admit sunlight, which is focused to a point on the receiving surface by a lens or set of lenses, over a wide range of solar angles. An analytic model for assessing device performance based on statistical ray optics is described and confirmed by raytrace simulations on a model system.
Chen, Min; Gu, Jiajun; Sun, Cheng; Zhao, Yixin; Zhang, Ruoxi; You, Xinyuan; Liu, Qinglei; Zhang, Wang; Su, Yishi; Su, Huilan; Zhang, Di
2016-07-26
Photoelectric conversion driven by sunlight has a broad range of energy/environmental applications (e.g., in solar cells and water splitting). However, difficulties are encountered in the separation of photoexcited charges. Here, we realize a long-range (∼1.5 μm period) electric polarization via asymmetric localization of surface plasmons on a three-dimensional silver structure (3D-Ag). This visible-light-responsive effect-the photo-Dember effect, can be analogous to the thermoelectric effect, in which hot carriers are thermally generated instead of being photogenerated. The induced electric field can efficiently separate photogenerated charges, enabling sunlight-driven overall water splitting on a series of dopant-free commercial semiconductor particles (i.e., ZnO, CeO2, TiO2, and WO3) once they are combined with the 3D-Ag substrate. These photocatalytic processes can last over 30 h on 3D-Ag+ZnO, 3D-Ag+CeO2, and 3D-Ag+TiO2, thus demonstrating good catalytic stability for these systems. Using commercial WO3 powder as a reference, the amount of O2 generated with 3D-Ag+CeO2 surpasses even its recently reported counterpart in which sacrificial reagents had to be involved to run half-reactions. This plasmon-mediated charge separation strategy provides an effective way to improve the efficiency of photoelectric energy conversion, which can be useful in photovoltaics and photocatalysis.
Chen, Min; Gu, Jiajun; Sun, Cheng; Zhao, Yixin; Zhang, Ruoxi; You, Xinyuan; Liu, Qinglei; Zhang, Wang; Su, Yishi; Su, Huilan; Zhang, Di
2016-07-26
Photoelectric conversion driven by sunlight has a broad range of energy/environmental applications (e.g., in solar cells and water splitting). However, difficulties are encountered in the separation of photoexcited charges. Here, we realize a long-range (∼1.5 μm period) electric polarization via asymmetric localization of surface plasmons on a three-dimensional silver structure (3D-Ag). This visible-light-responsive effect-the photo-Dember effect, can be analogous to the thermoelectric effect, in which hot carriers are thermally generated instead of being photogenerated. The induced electric field can efficiently separate photogenerated charges, enabling sunlight-driven overall water splitting on a series of dopant-free commercial semiconductor particles (i.e., ZnO, CeO2, TiO2, and WO3) once they are combined with the 3D-Ag substrate. These photocatalytic processes can last over 30 h on 3D-Ag+ZnO, 3D-Ag+CeO2, and 3D-Ag+TiO2, thus demonstrating good catalytic stability for these systems. Using commercial WO3 powder as a reference, the amount of O2 generated with 3D-Ag+CeO2 surpasses even its recently reported counterpart in which sacrificial reagents had to be involved to run half-reactions. This plasmon-mediated charge separation strategy provides an effective way to improve the efficiency of photoelectric energy conversion, which can be useful in photovoltaics and photocatalysis. PMID:27351779
Covalent Triazine-Based Frameworks as Visible Light Photocatalysts for the Splitting of Water.
Bi, Jinhong; Fang, Wei; Li, Liuyi; Wang, Jinyun; Liang, Shijing; He, Yunhui; Liu, Minghua; Wu, Ling
2015-10-01
Covalent triazine-based frameworks (CTFs) with a graphene-like layered morphology have been controllably synthesized by the trifluoromethanesulfonic acid-catalyzed nitrile trimerization reactions at room temperature via selecting different monomers. Platinum nanoparticles are well dispersed in CTF-T1, which is ascribed to the synergistic effects of the coordination of triazine moieties and the nanoscale confinement effect of CTFs. CTF-T1 exhibits excellent photocatalytic activity and stability for H2 evolution in the presence of platinum under visible light irradiation (λ ≥ 420 nm). The activity and stability of CTF-T1 are comparable to those of g-C3 N4 . Importantly, as a result of the tailorable electronic and spatial structures of CTFs that can be achieved through the judicial selection of monomers, CTFs not only show great potential as organic semiconductor for photocatalysis but also may provide a molecular-level understanding of the inherent heterogeneous photocatalysis.
Hyperfine splitting and the Zeeman effect in holographic heavy-light mesons
Herzog, Christopher P.; Stricker, Stefan A.; Vuorinen, Aleksi
2010-08-15
We inspect the mass spectrum of heavy-light mesons in deformed N=2 super Yang-Mills theory using the AdS/CFT correspondence. We demonstrate how some of the degeneracies of the supersymmetric meson spectrum can be removed upon breaking the supersymmetry, thus leading to the emergence of a hyperfine structure. The explicit SUSY breaking scenarios we consider involve on the one hand, tilting one of the two fundamental D7-branes inside the internal R{sup 6} space, and on the other hand, applying an external magnetic field on the (untilted) branes. The latter scenario leads to the well-known Zeeman effect, which we inspect for both weak and strong magnetic fields.
Erogbogbo, Folarin; Lin, Tao; Tucciarone, Phillip M; LaJoie, Krystal M; Lai, Larry; Patki, Gauri D; Prasad, Paras N; Swihart, Mark T
2013-02-13
We demonstrate that nanosize silicon (~10 nm diameter) reacts with water to generate hydrogen 1000 times faster than bulk silicon, 100 times faster than previously reported Si structures, and 6 times faster than competing metal formulations. The H(2) production rate using 10 nm Si is 150 times that obtained using 100 nm particles, dramatically exceeding the expected effect of increased surface to volume ratio. We attribute this to a change in the etching dynamics at the nanoscale from anisotropic etching of larger silicon to effectively isotropic etching of 10 nm silicon. These results imply that nanosilicon could provide a practical approach for on-demand hydrogen production without addition of heat, light, or electrical energy.
Zheng, Xue-Li; Song, Ji-Peng; Ling, Tao; Hu, Zhen Peng; Yin, Peng-Fei; Davey, Kenneth; Du, Xi-Wen; Qiao, Shi-Zhang
2016-06-01
T. Ling, X.-W. Du, S. Z. Qiao, and co-workers report strongly coupled Nafion molecules and ordered-porous CdS networks for visible-light water splitting. The image conceptually shows how the three-dimensional ordered structure effectively harvests incoming light. As described on page 4935, the inorganic CdS skeleton is homogeneously passivated by the organic Nafion molecules to facilitate hydrogen generation. PMID:27311095
Zheng, Xue-Li; Song, Ji-Peng; Ling, Tao; Hu, Zhen Peng; Yin, Peng-Fei; Davey, Kenneth; Du, Xi-Wen; Qiao, Shi-Zhang
2016-06-01
T. Ling, X.-W. Du, S. Z. Qiao, and co-workers report strongly coupled Nafion molecules and ordered-porous CdS networks for visible-light water splitting. The image conceptually shows how the three-dimensional ordered structure effectively harvests incoming light. As described on page 4935, the inorganic CdS skeleton is homogeneously passivated by the organic Nafion molecules to facilitate hydrogen generation.
Santinacci, Lionel; Diouf, Maïmouna W; Barr, Maïssa K S; Fabre, Bruno; Joanny, Loïc; Gouttefangeas, Francis; Loget, Gabriel
2016-09-21
Macroporous layers are grown onto n-type silicon by successive photoelectrochemical etching in HF-containing solution and chemical etching in KOH. This specific latter treatment gives highly antireflective properties of the Si surface. The duration of the chemical etching is optimized to render the surface as absorbent as possible, and the morphology of the as-grown layer is characterized by scanning electron microscopy. Further functionalization of such structured Si surface is carried out by atomic layer deposition of a thin conformal and homogeneous TiO2 layer that is crystallized by an annealing at 450 °C. This process allows using such surfaces as photoanodes for water oxidation. The 40 nm thick TiO2 film acts indeed as an efficient protective layer against the photocorrosion of the porous Si in KOH, enhances its wettability, and improves the light absorption of the photoelectrode. The macroporous dual-absorber TiO2/Si has a beneficial effect on water oxidation in 1 M KOH and leads to a considerable negative shift of the onset potential of ∼400 mV as well as a 50% increase in photocurrent at 1 V vs SCE. PMID:27575424
Atomic-Layer-Confined Doping for Atomic-Level Insights into Visible-Light Water Splitting.
Lei, Fengcai; Zhang, Lei; Sun, Yongfu; Liang, Liang; Liu, Katong; Xu, Jiaqi; Zhang, Qun; Pan, Bicai; Luo, Yi; Xie, Yi
2015-08-01
A model of doping confined in atomic layers is proposed for atomic-level insights into the effect of doping on photocatalysis. Co doping confined in three atomic layers of In2S3 was implemented with a lamellar hybrid intermediate strategy. Density functional calculations reveal that the introduction of Co ions brings about several new energy levels and increased density of states at the conduction band minimum, leading to sharply increased visible-light absorption and three times higher carrier concentration. Ultrafast transient absorption spectroscopy reveals that the electron transfer time of about 1.6 ps from the valence band to newly formed localized states is due to Co doping. The 25-fold increase in average recovery lifetime is believed to be responsible for the increased of electron-hole separation. The synthesized Co-doped In2S3 (three atomic layers) yield a photocurrent of 1.17 mA cm(-2) at 1.5 V vs. RHE, nearly 10 and 17 times higher than that of the perfect In2S3 (three atomic layers) and the bulk counterpart, respectively.
Santinacci, Lionel; Diouf, Maïmouna W; Barr, Maïssa K S; Fabre, Bruno; Joanny, Loïc; Gouttefangeas, Francis; Loget, Gabriel
2016-09-21
Macroporous layers are grown onto n-type silicon by successive photoelectrochemical etching in HF-containing solution and chemical etching in KOH. This specific latter treatment gives highly antireflective properties of the Si surface. The duration of the chemical etching is optimized to render the surface as absorbent as possible, and the morphology of the as-grown layer is characterized by scanning electron microscopy. Further functionalization of such structured Si surface is carried out by atomic layer deposition of a thin conformal and homogeneous TiO2 layer that is crystallized by an annealing at 450 °C. This process allows using such surfaces as photoanodes for water oxidation. The 40 nm thick TiO2 film acts indeed as an efficient protective layer against the photocorrosion of the porous Si in KOH, enhances its wettability, and improves the light absorption of the photoelectrode. The macroporous dual-absorber TiO2/Si has a beneficial effect on water oxidation in 1 M KOH and leads to a considerable negative shift of the onset potential of ∼400 mV as well as a 50% increase in photocurrent at 1 V vs SCE.
Chai, Zhigang; Zeng, Ting-Ting; Li, Qi; Lu, Liang-Qiu; Xiao, Wen-Jing; Xu, Dongsheng
2016-08-17
Splitting of alcohols into hydrogen and corresponding carbonyl compounds has potential applications in hydrogen production and chemical industry. Herein, we report that a heterogeneous photocatalyst (Ni-modified CdS nanoparticles) could efficiently split alcohols into hydrogen and corresponding aldehydes or ketones in a stoichiometric manner under visible light irradiation. Optimized apparent quantum yields of 38%, 46%, and 48% were obtained at 447 nm for dehydrogenation of methanol, ethanol, and 2-propanol, respectively. In the case of dehydrogenation of 2-propanol, a turnover number of greater than 44 000 was achieved. To our knowledge, these are unprecedented values for photocatalytic splitting of liquid alcohols under visible light to date. Besides, the current catalyst system functions well with other aliphatic and aromatic alcohols, affording the corresponding carbonyl compounds with good to excellent conversion and outstanding selectivity. Moreover, mechanistic investigations suggest that an interface between Ni nanocrystal and CdS plays a key role in the reaction mechanism of the photocatalytic splitting of alcohol. PMID:27477237
Removing sparse noise from hyperspectral images with sparse and low-rank penalties
NASA Astrophysics Data System (ADS)
Tariyal, Snigdha; Aggarwal, Hemant Kumar; Majumdar, Angshul
2016-03-01
In diffraction grating, at times, there are defective pixels on the focal plane array; this results in horizontal lines of corrupted pixels in some channels. Since only a few such pixels exist, the corruption/noise is sparse. Studies on sparse noise removal from hyperspectral noise are parsimonious. To remove such sparse noise, a prior work exploited the interband spectral correlation along with intraband spatial redundancy to yield a sparse representation in transform domains. We improve upon the prior technique. The intraband spatial redundancy is modeled as a sparse set of transform coefficients and the interband spectral correlation is modeled as a rank deficient matrix. The resulting optimization problem is solved using the split Bregman technique. Comparative experimental results show that our proposed approach is better than the previous one.
NASA Astrophysics Data System (ADS)
Asano, M.; Özdemir, Ş. K.; Chen, W.; Ikuta, R.; Yang, L.; Imoto, N.; Yamamoto, T.
2016-05-01
We report controllable manipulation of slow and fast light in a whispering-gallery-mode microtoroid resonator fabricated from Erbium (Er3+) doped silica. We observe continuous transition of the coupling between the fiber-taper waveguide and the microresonator from undercoupling to critical coupling and then to overcoupling regimes by increasing the pump power even though the spatial distance between the resonator and the waveguide was kept fixed. This, in turn, enables switching from fast to slow light and vice versa just by increasing the optical gain. An enhancement of delay of two-fold over the passive silica resonator (no optical gain) was observed in the slow light regime. Moreover, we show dynamic pulse splitting and its control in slow/fast light systems using optical gain.
Wang, Meng; Ren, Feng; Zhou, Jigang; Cai, Guangxu; Cai, Li; Hu, Yongfeng; Wang, Dongniu; Liu, Yichao; Guo, Liejin; Shen, Shaohua
2015-01-01
Solution-based ZnO nanorod arrays (NRAs) were modified with controlled N doping by an advanced ion implantation method, and were subsequently utilized as photoanodes for photoelectrochemical (PEC) water splitting under visible light irradiation. A gradient distribution of N dopants along the vertical direction of ZnO nanorods was realized. N doped ZnO NRAs displayed a markedly enhanced visible-light-driven PEC photocurrent density of ~160 μA/cm2 at 1.1 V vs. saturated calomel electrode (SCE), which was about 2 orders of magnitude higher than pristine ZnO NRAs. The gradiently distributed N dopants not only extended the optical absorption edges to visible light region, but also introduced terraced band structure. As a consequence, N gradient-doped ZnO NRAs can not only utilize the visible light irradiation but also efficiently drive photo-induced electron and hole transfer via the terraced band structure. The superior potential of ion implantation technique for creating gradient dopants distribution in host semiconductors will provide novel insights into doped photoelectrode materials for solar water splitting. PMID:26262752
Wang, Meng; Ren, Feng; Zhou, Jigang; Cai, Guangxu; Cai, Li; Hu, Yongfeng; Wang, Dongniu; Liu, Yichao; Guo, Liejin; Shen, Shaohua
2015-01-01
Solution-based ZnO nanorod arrays (NRAs) were modified with controlled N doping by an advanced ion implantation method, and were subsequently utilized as photoanodes for photoelectrochemical (PEC) water splitting under visible light irradiation. A gradient distribution of N dopants along the vertical direction of ZnO nanorods was realized. N doped ZnO NRAs displayed a markedly enhanced visible-light-driven PEC photocurrent density of ~160 μA/cm(2) at 1.1 V vs. saturated calomel electrode (SCE), which was about 2 orders of magnitude higher than pristine ZnO NRAs. The gradiently distributed N dopants not only extended the optical absorption edges to visible light region, but also introduced terraced band structure. As a consequence, N gradient-doped ZnO NRAs can not only utilize the visible light irradiation but also efficiently drive photo-induced electron and hole transfer via the terraced band structure. The superior potential of ion implantation technique for creating gradient dopants distribution in host semiconductors will provide novel insights into doped photoelectrode materials for solar water splitting. PMID:26262752
NASA Astrophysics Data System (ADS)
Klingler, S.; Maier-Flaig, H.; Gross, R.; Hu, C.-M.; Huebl, H.; Goennenwein, S. T. B.; Weiler, M.
2016-08-01
Microfocused Brillouin light scattering (BLS) and microwave absorption (MA) are used to study magnon-photon coupling in a system consisting of a split-ring microwave resonator and an yttrium iron garnet (YIG) film. The split-ring resonator is defined by optical lithography and loaded with a 1 μm-thick YIG film grown by liquid phase epitaxy. BLS and MA spectra of the hybrid system are simultaneously recorded as a function of the applied magnetic field magnitude and microwave excitation frequency. Strong coupling of the magnon and microwave resonator modes is found with a coupling strength of geff /2π = 63 MHz. The combined BLS and MA data allow us to study the continuous transition of the hybridized modes from a purely magnonic to a purely photonic mode by varying the applied magnetic field and microwave frequency. Furthermore, the BLS data represent an up-conversion of the microwave frequency coupling to optical frequencies.
Sparse Regression as a Sparse Eigenvalue Problem
NASA Technical Reports Server (NTRS)
Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai
2008-01-01
We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization
Hsieh, S H; Lee, G J; Chen, C Y; Chen, J H; Ma, S H; Horng, T L; Chen, K H; Wu, J J
2012-07-01
This study was focused on the preparation of modified bismuth oxide photocatalysts, including Ru and Pt doped Bi2O3, using sonochemically assisted method to enhance their photocatalytic activity. The crystalline phase composition and surface structure of Bi2O3 photocatalysts were examined using SEM, XRD, UV-visible spectroscopy, and XPS. Optical characterizations have indicated that the Bi2O3 presents the photoabsorption properties shifting from UV light region into visible light which is approaching towards the edge of 470 nm. According to the experimental results, visible-light-driven photocatalysis for water splitting with the addition of 0.3 M Na2SO3 and 0.03 M H2C2O4 as sacrificing agents demonstrates that Pt/Bi2O3-RuO2 catalyst could increase the amount of hydrogen evolution, which is around 11.6 and 14.5 micromol g(-1) h(-1), respectively. Plausible formation mechanisms of modified bismuth oxide and reaction mechanisms of photocatalytic water splitting have been proposed. PMID:22966683
Sun, Yi-Yang; Zhang, Shengbai
2016-01-28
Using density functional theory calculation we investigate the carbon doping of anatase TiO2, a technique widely studied for visible-light driven water splitting. By a detailed analysis of the thermodynamics of C defects in TiO2, we show that any significant concentration of C dopants in the TiO2 lattice must be a result of non-equilibrium doping, which emphasizes the importance of kinetics stabilized C defects. Based on the band gaps calculated using hybrid density functionals, we exclude the possibility of C occupying Ti lattice sites or interstitial sites to enhance visible-light absorption of TiO2, as extensively discussed in the literature. Also, the recently proposed defect with a CO species occupying two O sites yields a too small band gap for water splitting. Two defects that can effectively reduce the band gap for the water splitting application are identified to be: (1) the CO-VO complex, i.e., a C substituting for O (CO) paired with an O vacancy (VO) and (2) the (C2)2O complex with a C dimer (C2) occupying two neighboring O vacancies. Compared with the CO-VO complex, (C2)2O exhibits strong binding (greater than 2.5 eV) between the two C atoms, which could significantly enhance its kinetic stability to survive from high temperature annealing. With a reduced band gap of about 1.4 eV, carbon dimers could be ideal for kinetic doping of anatase TiO2 to enhance its visible-light activity in photocatalytic reactions. Molecular doping using C2H2 or C2H4 as C precursors has been proposed to introduce the carbon dimers into TiO2.
Dillert, Ralf; Taffa, Dereje H.; Wark, Michael; Bredow, Thomas; Bahnemann, Detlef W.
2015-10-01
The utilization of solar light for the photoelectrochemical and photocatalytic production of molecular hydrogen from water is a scientific and technical challenge. Semiconductors with suitable properties to promote solar-driven water splitting are a desideratum. A hitherto rarely investigated group of semiconductors are ferrites with the empirical formula MFe{sub 2}O{sub 4} and related compounds. This contribution summarizes the published results of the experimental investigations on the photoelectrochemical and photocatalytic properties of these compounds. It will be shown that the potential of this group of compounds in regard to the production of solar hydrogen has not been fully explored yet.
Zhong, Yuqing; Ueno, Kosei; Mori, Yuko; Shi, Xu; Oshikiri, Tomoya; Murakoshi, Kei; Inoue, Haruo; Misawa, Hiroaki
2014-09-22
A plasmon-induced water splitting system that operates under irradiation by visible light was successfully developed; the system is based on the use of both sides of the same strontium titanate (SrTiO3) single-crystal substrate. The water splitting system contains two solution chambers to separate hydrogen (H2) and oxygen (O2). To promote water splitting, a chemical bias was applied by regulating the pH values of the chambers. The quantity of H2 evolved from the surface of platinum, which was used as a reduction co-catalyst, was twice the quantity of O2 evolved from an Au-nanostructured surface. Thus, the stoichiometric evolution of H2 and O2 was clearly demonstrated. The hydrogen-evolution action spectrum closely corresponds to the plasmon resonance spectrum, indicating that the plasmon-induced charge separation at the Au/SrTiO3 interface promotes water oxidation and the subsequent reduction of a proton on the backside of the SrTiO3 substrate. The chemical bias is significantly reduced by plasmonic effects, which indicates the possibility of constructing an artificial photosynthesis system with low energy consumption. PMID:24988943
Finding Nonoverlapping Substructures of a Sparse Matrix
Pinar, Ali; Vassilevska, Virginia
2005-08-11
Many applications of scientific computing rely on computations on sparse matrices. The design of efficient implementations of sparse matrix kernels is crucial for the overall efficiency of these applications. Due to the high compute-to-memory ratio and irregular memory access patterns, the performance of sparse matrix kernels is often far away from the peak performance on a modern processor. Alternative data structures have been proposed, which split the original matrix A into A{sub d} and A{sub s}, so that A{sub d} contains all dense blocks of a specified size in the matrix, and A{sub s} contains the remaining entries. This enables the use of dense matrix kernels on the entries of A{sub d} producing better memory performance. In this work, we study the problem of finding a maximum number of nonoverlapping dense blocks in a sparse matrix, which is previously not studied in the sparse matrix community. We show that the maximum nonoverlapping dense blocks problem is NP-complete by using a reduction from the maximum independent set problem on cubic planar graphs. We also propose a 2/3-approximation algorithm that runs in linear time in the number of nonzeros in the matrix. This extended abstract focuses on our results for 2x2 dense blocks. However we show that our results can be generalized to arbitrary sized dense blocks, and many other oriented substructures, which can be exploited to improve the memory performance of sparse matrix operations.
NASA Astrophysics Data System (ADS)
Wang, Degao; Chang, Guoliang; Zhang, Yuying; Chao, Jie; Yang, Jianzhong; Su, Shao; Wang, Lihua; Fan, Chunhai; Wang, Lianhui
2016-06-01
Herein, we presented hierarchical three-dimensional (3D) branched hematite nanorod arrays (NAs) on transparent fluorine-doped tin oxide (FTO) conductive glass substrates, which exhibited high PEC water splitting performance due to the enhancement of mid-visible light harvesting as well as charge separation and transfer. The introduction of a TiO2 underlayer made the as-prepared 3D branched hematite NAs achieve a photocurrent density of 0.61 mA cm-2 at 1.23 V vs. reversible hydrogen electrode (RHE) without high-temperature activation.Herein, we presented hierarchical three-dimensional (3D) branched hematite nanorod arrays (NAs) on transparent fluorine-doped tin oxide (FTO) conductive glass substrates, which exhibited high PEC water splitting performance due to the enhancement of mid-visible light harvesting as well as charge separation and transfer. The introduction of a TiO2 underlayer made the as-prepared 3D branched hematite NAs achieve a photocurrent density of 0.61 mA cm-2 at 1.23 V vs. reversible hydrogen electrode (RHE) without high-temperature activation. Electronic supplementary information (ESI) available: Experimental details. See DOI: 10.1039/c6nr03855g
Zhang, Zhonghai; Zhang, Lianbin; Hedhili, Mohamed Nejib; Zhang, Hongnan; Wang, Peng
2013-01-01
A visible light responsive plasmonic photocatalytic composite material is designed by rationally selecting Au nanocrystals and assembling them with the TiO(2)-based photonic crystal substrate. The selection of the Au nanocrystals is so that their surface plasmonic resonance (SPR) wavelength matches the photonic band gap of the photonic crystal and thus that the SPR of the Au receives remarkable assistance from the photonic crystal substrate. The design of the composite material is expected to significantly increase the Au SPR intensity and consequently boost the hot electron injection from the Au nanocrystals into the conduction band of TiO(2), leading to a considerably enhanced water splitting performance of the material under visible light. A proof-of-concept example is provided by assembling 20 nm Au nanocrystals, with a SPR peak at 556 nm, onto the photonic crystal which is seamlessly connected on TiO(2) nanotube array. Under visible light illumination (>420 nm), the designed material produced a photocurrent density of ~150 μA cm(-2), which is the highest value ever reported in any plasmonic Au/TiO(2) system under visible light irradiation due to the photonic crystal-assisted SPR. This work contributes to the rational design of the visible light responsive plasmonic photocatalytic composite material based on wide band gap metal oxides for photoelectrochemical applications.
High performance Au-Cu alloy for enhanced visible-light water splitting driven by coinage metals.
Liu, Mingyang; Zhou, Wei; Wang, Ting; Wang, Defa; Liu, Lequan; Ye, Jinhua
2016-03-28
A Au-Cu alloy strategy is, for the first time, demonstrated to be effective in enhancing visible-light photocatalytic H2 evolution via promoting metal interband transitions. Au3Cu/SrTiO3, in which oxidation of Cu was successfully restrained, showed the highest visible-light H2 evolution activity.
High performance Au-Cu alloy for enhanced visible-light water splitting driven by coinage metals.
Liu, Mingyang; Zhou, Wei; Wang, Ting; Wang, Defa; Liu, Lequan; Ye, Jinhua
2016-03-28
A Au-Cu alloy strategy is, for the first time, demonstrated to be effective in enhancing visible-light photocatalytic H2 evolution via promoting metal interband transitions. Au3Cu/SrTiO3, in which oxidation of Cu was successfully restrained, showed the highest visible-light H2 evolution activity. PMID:26952932
Ge, Ming-Zheng; Cao, Chun-Yan; Li, Shu-Hui; Tang, Yu-Xin; Wang, Lu-Ning; Qi, Ning; Huang, Jian-Ying; Zhang, Ke-Qin; Al-Deyab, S S; Lai, Yue-Kun
2016-03-01
An ultrasonication-assisted in situ deposition strategy was utilised to uniformly decorate plasmonic Ag nanoparticles on vertically aligned TiO2 nanotube arrays (NTAs) to construct a Ag@TiO2 NTA composite. The Ag nanoparticles act as efficient surface plasmon resonance (SPR) photosensitizers to drive photocatalytic water splitting under visible light irradiation. The Ag nanoparticles were uniformly deposited on the surface and inside the highly oriented TiO2 nanotubes. The visible-light-driven hydrogen production activities of silver nanoparticle anchored TiO2 nanotube array photocatalysts were evaluated using methanol as a sacrificial reagent in water under a 500 W Xe lamp with a UV light cutoff filter (λ ≥ 420 nm). It was found that the hydrogen production rate of the Ag@TiO2 NTAs prepared with ultrasonication-assisted deposition for 5 min was approximately 15 times higher than that of its pristine TiO2 NTAs counterpart. The highly efficient photocatalytic hydrogen evolution is attributed to the SPR effect of Ag for enhanced visible light absorption and boosting the photogenerated electron-hole separation/transfer. This strategy is promising for the design and construction of high efficiency TiO2 based photocatalysts for solar energy conversion. PMID:26878901
Xiong, Zuzhou; Zheng, Maojun; Zhu, Changqing; Zhang, Bin; Ma, Li; Shen, Wenzhong
2013-01-01
Visible light accounts for about 43% of the solar spectrum, and developing highly efficient visible-light-driven photocatalyst is of special significance. In this work, highly efficient three-dimensional (3D) Cd1-xZnxS photocatalysts for hydrogen generation under the irradiation of visible light were synthesized via one-step solvothermal pathway. Scanning electron microscope, X-ray diffractometer, Raman spectrometer, and X-ray photoelectron spectrometer were utilized to characterize the morphology, crystal structure, vibrational states, and surface composition of the obtained 3D Cd1-xZnxS. UV-Vis spectra indicated that the as-synthesized Cd1-xZnxS had appropriate bandgap and position of the conduction band that is beneficial for visible light absorption and photo-generated electron-hole pair separation. Moreover, the 3D structure offers a larger surface area thus supplying more surface reaction sites and better charge transport environment, and therefore, the efficiency of water splitting was improved further. PMID:23883429
Higashi, Masanobu; Yamanaka, Yuta; Tomita, Osamu; Abe, Ryu
2015-10-01
A series of cation-doped BaTaO{sub 2}N particle was synthesized to control the donor density in the bulk for improving the performance of photoelectrochemical water splitting on porous BaTaO{sub 2}N photoanodes under visible light. Among the dopants (Mo{sup 6+}, W{sup 6+}, Zr{sup 4+}, and Ti{sup 4+}) examined, Mo{sup 6+} cations can be introduced into the Ta{sup 5+} site up to 5 mol. % without producing any impurity phases; the donor density of BaTaO{sub 2}N was indeed increased significantly by introducing higher ratio of Mo{sup 6+} dopant. The porous photoanodes of Mo-doped BaTaO{sub 2}N showed much higher photocurrent than others including undoped one and also exhibited much improved performance in photoelectrochemical water splitting into H{sub 2} and O{sub 2} after loaded with cobalt oxide cocatalyst and coupled with Pt counter electrode.
Finding nonoverlapping substructures of a sparse matrix
Pinar, Ali; Vassilevska, Virginia
2004-08-09
Many applications of scientific computing rely on computations on sparse matrices, thus the design of efficient implementations of sparse matrix kernels is crucial for the overall efficiency of these applications. Due to the high compute-to-memory ratio and irregular memory access patterns, the performance of sparse matrix kernels is often far away from the peak performance on a modern processor. Alternative data structures have been proposed, which split the original matrix A into A{sub d} and A{sub s}, so that A{sub d} contains all dense blocks of a specified size in the matrix, and A{sub s} contains the remaining entries. This enables the use of dense matrix kernels on the entries of A{sub d} producing better memory performance. In this work, we study the problem of finding a maximum number of non overlapping rectangular dense blocks in a sparse matrix, which has not been studied in the sparse matrix community. We show that the maximum non overlapping dense blocks problem is NP-complete by using a reduction from the maximum independent set problem on cubic planar graphs. We also propose a 2/3-approximation algorithm for 2 times 2 blocks that runs in linear time in the number of nonzeros in the matrix. We discuss alternatives to rectangular blocks such as diagonal blocks and cross blocks and present complexity analysis and approximation algorithms.
Sparse pseudospectral approximation method
NASA Astrophysics Data System (ADS)
Constantine, Paul G.; Eldred, Michael S.; Phipps, Eric T.
2012-07-01
Multivariate global polynomial approximations - such as polynomial chaos or stochastic collocation methods - are now in widespread use for sensitivity analysis and uncertainty quantification. The pseudospectral variety of these methods uses a numerical integration rule to approximate the Fourier-type coefficients of a truncated expansion in orthogonal polynomials. For problems in more than two or three dimensions, a sparse grid numerical integration rule offers accuracy with a smaller node set compared to tensor product approximation. However, when using a sparse rule to approximately integrate these coefficients, one often finds unacceptable errors in the coefficients associated with higher degree polynomials. By reexamining Smolyak's algorithm and exploiting the connections between interpolation and projection in tensor product spaces, we construct a sparse pseudospectral approximation method that accurately reproduces the coefficients of basis functions that naturally correspond to the sparse grid integration rule. The compelling numerical results show that this is the proper way to use sparse grid integration rules for pseudospectral approximation.
A Multicast Sparse-Grooming Algorithm Based on Network Coding in WDM Networks
NASA Astrophysics Data System (ADS)
Zhang, Shengfeng; Peng, Han; Sui, Meng; Liu, Huanlin
2015-03-01
To improve the limited number of wavelength utilization and decrease the traffic blocking probability in sparse-grooming wavelength-division multiplexing (WDM) networks, a multicast sparse-grooming algorithm based on network coding (MCSA-NC) is put forward to solve the routing problem for dynamic multicast requests in this paper. In the proposed algorithm, a traffic partition strategy, that the coarse-granularity multicast request with grooming capability on the source node is split into several fine-granularity multicast requests, is designed so as to increase the probability for traffic grooming successfully in MCSA-NC. Besides considering that multiple destinations should receive the data from source of the multicast request at the same time, the traditional transmission mechanism is improved by constructing edge-disjoint paths for each split multicast request. Moreover, in order to reduce the number of wavelengths required and further decrease the traffic blocking probability, a light-tree reconfiguration mechanism is presented in the MCSA-NC, which can select a minimal cost light tree from the established edge-disjoint paths for a new multicast request.
Blum, Thomas; Doi, Takumi; Hayakawa, Masashi; Izubuchi, Taku; Yamada, Norikazu
2007-12-01
We determine the light quark masses from lattice QCD simulations incorporating the electromagnetic interaction of valence quarks, using the splittings of charged and neutral pseudoscalar meson masses as inputs. The meson masses are calculated on lattice QCD configurations generated by the RBC Collaboration for two flavors of dynamical domain-wall fermions, which are combined with QED configurations generated via quenched noncompact lattice QED. The electromagnetic part of the pion mass splitting is found to be m{sub {pi}{sup +}}-m{sub {pi}{sup 0}}=4.12(21) MeV, where only the statistical error is quoted, and similarly for the kaon, 1.443(55) MeV. Our results for the light quark masses are m{sub u}{sup MS}(2 GeV)=3.02(27)(19) MeV, m{sub d}{sup MS}(2 GeV)=5.49(20)(34) MeV, and m{sub s}{sup MS}(2 GeV)=119.5(56)(74) MeV, where the first error is statistical and the second reflects the uncertainty in our nonperturbative renormalization procedure. By averaging over {+-}e to cancel O(e) noise exactly on each combined gauge field configuration, we are able to work at physical {alpha}=1/137 and obtain very small statistical errors. In our calculation, several sources of systematic error remain, including finite volume, nonzero lattice spacing, chiral extrapolation, quenched QED, and quenched strange quark, which may be more significant than the errors quoted above. We discuss these systematic errors and how to reduce or eliminate them.
Nikolis, Andreas; Bernstein, Steven; Kinney, Brian; Scuderi, Nicolo; Rastogi, Shipra; Sampalis, John S
2016-01-01
Purpose Many treatment modalities exist to counteract the effects of cutaneous aging. Ablative methods have been the mainstay for nonsurgical facial rejuvenation. In recent years, nonablative techniques have been developed with the aim of achieving facial rejuvenation without epidermal damage. Light-emitting diode (LED) photorejuvenation is a novel nonablative technique that induces collagen synthesis through biophotomodulatory pathways. Materials and methods A single-center, randomized, single-blinded, placebo-controlled, split-faced clinical trial was designed. Thirty-two patients were enrolled for a 12-week study. Patients were randomized into one of four groups: Group A, treatment with KLOX-001 gel formulation and white LED (placebo) light; Group B, treatment with a placebo/base gel (no active chromophore) formulation and KLOX LED light; Group C, treatment with KLOX-001 gel formulation and KLOX LED light; and Group D, treatment with the standard skin rejuvenating treatment (0.1% retinol-based cream). Patients received treatment at weeks 0, 1, 2, and 3, and returned to the clinic at weeks 4, 8, and 12 for clinical assessments performed by an independent, blinded committee of physicians using subjective clinician assessment scales. Tolerability, adverse outcomes, and patient satisfaction were also assessed. Results Analysis demonstrated that the KLOX LED light with KLOX placebo/base gel and the KLOX LED light + KLOX-001 gel formulation groups were superior to standard of care and KLOX-001 gel formulation with placebo light on subjective clinical assessment and multiple wrinkle scales, with statistically significant results obtained for brow positioning, perioral wrinkling, and total wrinkle score. Conclusion The study results show that KLOX LED light with KLOX-001 gel formulation and KLOX LED light with KLOX placebo/base gel are effective, safe, well-tolerated, and painless treatment modalities for skin rejuvenation. PMID:27257391
NASA Astrophysics Data System (ADS)
Ge, Ming-Zheng; Cao, Chun-Yan; Li, Shu-Hui; Tang, Yu-Xin; Wang, Lu-Ning; Qi, Ning; Huang, Jian-Ying; Zhang, Ke-Qin; Al-Deyab, S. S.; Lai, Yue-Kun
2016-02-01
An ultrasonication-assisted in situ deposition strategy was utilised to uniformly decorate plasmonic Ag nanoparticles on vertically aligned TiO2 nanotube arrays (NTAs) to construct a Ag@TiO2 NTA composite. The Ag nanoparticles act as efficient surface plasmon resonance (SPR) photosensitizers to drive photocatalytic water splitting under visible light irradiation. The Ag nanoparticles were uniformly deposited on the surface and inside the highly oriented TiO2 nanotubes. The visible-light-driven hydrogen production activities of silver nanoparticle anchored TiO2 nanotube array photocatalysts were evaluated using methanol as a sacrificial reagent in water under a 500 W Xe lamp with a UV light cutoff filter (λ >= 420 nm). It was found that the hydrogen production rate of the Ag@TiO2 NTAs prepared with ultrasonication-assisted deposition for 5 min was approximately 15 times higher than that of its pristine TiO2 NTAs counterpart. The highly efficient photocatalytic hydrogen evolution is attributed to the SPR effect of Ag for enhanced visible light absorption and boosting the photogenerated electron-hole separation/transfer. This strategy is promising for the design and construction of high efficiency TiO2 based photocatalysts for solar energy conversion.An ultrasonication-assisted in situ deposition strategy was utilised to uniformly decorate plasmonic Ag nanoparticles on vertically aligned TiO2 nanotube arrays (NTAs) to construct a Ag@TiO2 NTA composite. The Ag nanoparticles act as efficient surface plasmon resonance (SPR) photosensitizers to drive photocatalytic water splitting under visible light irradiation. The Ag nanoparticles were uniformly deposited on the surface and inside the highly oriented TiO2 nanotubes. The visible-light-driven hydrogen production activities of silver nanoparticle anchored TiO2 nanotube array photocatalysts were evaluated using methanol as a sacrificial reagent in water under a 500 W Xe lamp with a UV light cutoff filter (λ >= 420 nm
Andersen, Torben B
2016-05-01
In a recent paper, conditions for achieving equal and opposite angular deflections of a light beam by reflection and refraction at an interface between air and a dielectric were determined [J. Opt. Soc. Am. A32, 2436 (2015)JOAOD60740-323210.1364/JOSAA.32.002436]. The paper gives plots of angles of incidence and refraction as a function of the prism refractive index as well as plots of reflectances and incident linear-polarization azimuth angles as functions of the refractive index. We show here that it is possible to express these quantities as simple algebraic functions of the refractive index.
NASA Astrophysics Data System (ADS)
Luo, Jie; Chen, Jiaoyan; Wang, Haiyan; Liu, Huangqing
2016-01-01
Visible-light-driven responsive Au/TiO2 nanotube arrays nanocomposites (LE-Au/TNTs) are prepared by depositing self-assembled monolayer of 3-mercaptopropionic acid (MPA) inside TNTs and then removing the ligands on the surface of Au through direct ligand-exchange method, which is beneficial for formation of intimate Au/TNTs Schottky contact after a mild annealing process. Under visible light illumination (λ > 400 nm), the photocurrent density of LE-Au/TNTs is 202 μA/cm2, which is the highest value ever reported in Au/TiO2 systems. Moreover, the incident photon to current conversion efficiency (IPCE) of LE-Au/TNTs at surface plasmonic resonance induced absorption peak (555 nm) is 7.4%. It is worth noted that the hydrogen evolution rates of the LE-Au/TNTs under simulated solar irradiation (AM1.5G, 100 mW/cm2) are 22.5 μmol/h, which is much higher than that of pristine TNTs (8.1 μmol/h). In addition, the LE-Au/TNTs show higher photoelectrochemical water splitting performance than the Au/TNTs prepared by direct impregnation-precipitation (IPAu/TNTs) strategy, which is ascribed to the close Schottky contact between Au and TNTs for better charge separation and transfer.
Hernández, Simelys; Cauda, Valentina; Chiodoni, Angelica; Dallorto, Stefano; Sacco, Adriano; Hidalgo, Diana; Celasco, Edvige; Pirri, Candido Fabrizio
2014-08-13
A fast and low-cost sol-gel synthesis used to deposit a shell of TiO2 anatase onto an array of vertically aligned ZnO nanowires (NWs) is reported in this paper. The influence of the annealing atmosphere (air or N2) and of the NWs preannealing process, before TiO2 deposition, on both the physicochemical characteristics and photoelectrochemical (PEC) performance of the resulting heterostructure, was studied. The efficient application of the ZnO@TiO2 core-shells for the PEC water-splitting reaction, under simulated solar light illumination (AM 1.5G) solar light illumination in basic media, is here reported for the first time. This application has had a dual function: to enhance the photoactivity of pristine ZnO NWs and to increase the photodegradation stability, because of the protective role of the TiO2 shell. It was found that an air treatment induces a better charge separation and a lower carrier recombination, which in turn are responsible for an improvement in the PEC performance with respect to N2-treated core-shell materials. Finally, a photocurrent of 0.40 mA/cm(2) at 1.23 V versus RHE (2.2 times with respect to the pristine ZnO NWs) was obtained. This achievement can be regarded as a valuable result, considering similar nanostructured electrodes reported in the literature for this application.
NASA Astrophysics Data System (ADS)
Gross, P. A.; Javahiraly, N.; Geraldini Sabat, N.; Cottineau, T.; Savinova, E. R.; Keller, V.
2016-10-01
Vertically aligned TiO2 nanotubes (TiO2-NTs), obtained by anodization in organic electrolyte, are decorated with 15 nm Ag nanoparticles prepared by a micro-wave assisted polyol synthesis. The Ag/TiO2 system is characterized by electronic microscopies in order to build a Finite Differential Time Domain (FDTD) model to simulate the interaction of light with the system. By combining UV-visible spectroscopy and FDTD simulations, the observed red shift in the surface plasmon resonance wavelength of the Ag nanoparticles, deposited on TiO2, is explained. The Ag/TiO2-NT system is used as photoanode in a photoelectrochemical water splitting setup and shows an increasing Incident Photon to Current Conversion Efficiency (IPCE) in the visible light domain with an increasing amount of deposited Ag. The spectral position of this activity enhancement coincides with the one expected from the FDTD calculations for the surface plasmon resonance of the Ag nanoparticles deposited on TiO2.
Petranto, J.J.
1989-09-05
A split gland having only three parts is described. The gland has substantially the same stability to the relative motion of the constituent half-gland members during the attachment process to a female fitting as have more complicated designs. Ease of manufacture and use result from the reduction in complexity of the present invention. 15 figs.
Petranto, Joseph J.
1989-01-01
A split gland having only three parts is described. The gland has substantially the same stability to the relative motion of the constituent half-gland members during the attachment process to a female fitting as have more complicated designs. Ease of manufacture and use result from the reduction in complexity of the present invention.
Kosaka, Sachiko; Yasumoto, Minako; Akilov, Oleg E; Hasan, Tayyaba; Kawana, Seiji
2010-12-01
Photodynamic therapy (PDT) with 5-aminolevulinic acid (ALA) (ALA-PDT) using intense pulsed light (IPL) as a light source (IPL-ALA-PDT) has been used for photorejuvenation, but it is unclear if this protocol can be applied to darker skin types. We performed this study to assess our IPL-ALA-PDT protocol for photorejuvenation in Asian skin. To determine an appropriate dose, ALA ointment (0-20%) was applied to the upper arm of five healthy volunteers and the fluorescence intensity (FI) was measured using a spectrofluorometer. Non-linear regression analysis of FI 2 h after ALA application with global fitting gave a typical sigmoid dose-response curve with R² = 0.9705 and saturation after 5% ALA. The entire faces of 16 Japanese women with photodamage were then treated with IPL (500-670 and 870-1400 nm, 23-30 J/cm²) 2 h after application of 5% ALA to one side of the face. Three treatments were delivered at 4-week intervals with follow-up visits. Comparative analysis of photorejuvenation showed noticeable improvements on both sides of the face, although the reduction in the photoaging score from baseline did not differ significantly between the two sides in all subjects. Despite this finding, 75% of the patients felt that the IPL-ALA-PDT-treated side of the face showed greater improvement than the IPL-treated side. However, all IPL-ALA-PDT-treated sides showed adverse effects such as erythema and pain. Therefore, we conclude that the IPL-ALA-PDT protocol requires optimization for photorejuvenation in Asians.
Group-based sparse representation for image restoration.
Zhang, Jian; Zhao, Debin; Gao, Wen
2014-08-01
Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception.
SAR Image Despeckling Via Structural Sparse Representation
NASA Astrophysics Data System (ADS)
Lu, Ting; Li, Shutao; Fang, Leyuan; Benediktsson, Jón Atli
2016-12-01
A novel synthetic aperture radar (SAR) image despeckling method based on structural sparse representation is introduced. The proposed method utilizes the fact that different regions in SAR images correspond to varying terrain reflectivity. Therefore, SAR images can be split into a heterogeneous class (with a varied terrain reflectivity) and a homogeneous class (with a constant terrain reflectivity). In the proposed method, different sparse representation based despeckling schemes are designed by combining the different region characteristics in SAR images. For heterogeneous regions with rich structure and texture information, structural dictionaries are learned to appropriately represent varied structural characteristics. Specifically, each patch in these regions is sparsely coded with the best fitted structural dictionary, thus good structure preservation can be obtained. For homogenous regions without rich structure and texture information, the highly redundant photometric self-similarity is exploited to suppress speckle noise without introducing artifacts. That is achieved by firstly learning the sub-dictionary, then simultaneously sparsely coding for each group of photometrically similar image patches. Visual and objective experimental results demonstrate the superiority of the proposed method over the-state-of-the-art methods.
A Comparative Study of Sparse Associative Memories
NASA Astrophysics Data System (ADS)
Gripon, Vincent; Heusel, Judith; Löwe, Matthias; Vermet, Franck
2016-07-01
We study various models of associative memories with sparse information, i.e. a pattern to be stored is a random string of 0s and 1s with about log N 1s, only. We compare different synaptic weights, architectures and retrieval mechanisms to shed light on the influence of the various parameters on the storage capacity.
Sparse distributed memory overview
NASA Technical Reports Server (NTRS)
Raugh, Mike
1990-01-01
The Sparse Distributed Memory (SDM) project is investigating the theory and applications of massively parallel computing architecture, called sparse distributed memory, that will support the storage and retrieval of sensory and motor patterns characteristic of autonomous systems. The immediate objectives of the project are centered in studies of the memory itself and in the use of the memory to solve problems in speech, vision, and robotics. Investigation of methods for encoding sensory data is an important part of the research. Examples of NASA missions that may benefit from this work are Space Station, planetary rovers, and solar exploration. Sparse distributed memory offers promising technology for systems that must learn through experience and be capable of adapting to new circumstances, and for operating any large complex system requiring automatic monitoring and control. Sparse distributed memory is a massively parallel architecture motivated by efforts to understand how the human brain works. Sparse distributed memory is an associative memory, able to retrieve information from cues that only partially match patterns stored in the memory. It is able to store long temporal sequences derived from the behavior of a complex system, such as progressive records of the system's sensory data and correlated records of the system's motor controls.
LOFAR sparse image reconstruction
NASA Astrophysics Data System (ADS)
Garsden, H.; Girard, J. N.; Starck, J. L.; Corbel, S.; Tasse, C.; Woiselle, A.; McKean, J. P.; van Amesfoort, A. S.; Anderson, J.; Avruch, I. M.; Beck, R.; Bentum, M. J.; Best, P.; Breitling, F.; Broderick, J.; Brüggen, M.; Butcher, H. R.; Ciardi, B.; de Gasperin, F.; de Geus, E.; de Vos, M.; Duscha, S.; Eislöffel, J.; Engels, D.; Falcke, H.; Fallows, R. A.; Fender, R.; Ferrari, C.; Frieswijk, W.; Garrett, M. A.; Grießmeier, J.; Gunst, A. W.; Hassall, T. E.; Heald, G.; Hoeft, M.; Hörandel, J.; van der Horst, A.; Juette, E.; Karastergiou, A.; Kondratiev, V. I.; Kramer, M.; Kuniyoshi, M.; Kuper, G.; Mann, G.; Markoff, S.; McFadden, R.; McKay-Bukowski, D.; Mulcahy, D. D.; Munk, H.; Norden, M. J.; Orru, E.; Paas, H.; Pandey-Pommier, M.; Pandey, V. N.; Pietka, G.; Pizzo, R.; Polatidis, A. G.; Renting, A.; Röttgering, H.; Rowlinson, A.; Schwarz, D.; Sluman, J.; Smirnov, O.; Stappers, B. W.; Steinmetz, M.; Stewart, A.; Swinbank, J.; Tagger, M.; Tang, Y.; Tasse, C.; Thoudam, S.; Toribio, C.; Vermeulen, R.; Vocks, C.; van Weeren, R. J.; Wijnholds, S. J.; Wise, M. W.; Wucknitz, O.; Yatawatta, S.; Zarka, P.; Zensus, A.
2015-03-01
Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various deconvolution and minimization methods. Aims: Recent papers have established a clear link between the discrete nature of radio interferometry measurement and the "compressed sensing" (CS) theory, which supports sparse reconstruction methods to form an image from the measured visibilities. Empowered by proximal theory, CS offers a sound framework for efficient global minimization and sparse data representation using fast algorithms. Combined with instrumental direction-dependent effects (DDE) in the scope of a real instrument, we developed and validated a new method based on this framework. Methods: We implemented a sparse reconstruction method in the standard LOFAR imaging tool and compared the photometric and resolution performance of this new imager with that of CLEAN-based methods (CLEAN and MS-CLEAN) with simulated and real LOFAR data. Results: We show that i) sparse reconstruction performs as well as CLEAN in recovering the flux of point sources; ii) performs much better on extended objects (the root mean square error is reduced by a factor of up to 10); and iii) provides a solution with an effective angular resolution 2-3 times better than the CLEAN images. Conclusions: Sparse recovery gives a correct photometry on high dynamic and wide-field images and improved realistic structures of extended sources (of simulated and real LOFAR datasets). This sparse reconstruction method is compatible with modern interferometric imagers that handle DDE corrections (A- and W-projections) required for current and future instruments such as LOFAR and SKA.
CO2 splitting by H2O to CO and O2 under UV light in TiMCM-41silicate sieve
Lin, Wenyong; Han, Hongxian; Frei, Heinz
2004-04-06
The 266 nm light-induced reaction of CO{sub 2} and H{sub 2}O gas mixtures (including isotopic modifications {sup 13}CO{sub 2}, C{sup 18}O{sub 2}, and D{sub 2}O) in framework TiMCM-41 silicate sieve was monitored by in-situ FT-IR spectroscopy at room temperature. Carbon monoxide gas was observed as the sole product by infrared, and the growth was found to depend linearly on the photolysis laser power. H{sub 2}O was confirmed as stoichiometric electron donor. The work establishes CO as the single photon, 2-electron transfer product of CO{sub 2} photoreduction by H{sub 2}O at framework Ti centers for the first time. O{sub 2} was detected as co-product by mass spectrometric analysis of the photolysis gas mixture. These results are explained by single UV photon-induced splitting of CO{sub 2} by H{sub 2}O to CO and surface OH radical.
Caccamo, Lorenzo; Hartmann, Jana; Fàbrega, Cristian; Estradé, Sonia; Lilienkamp, Gerhard; Prades, Joan Daniel; Hoffmann, Martin W G; Ledig, Johannes; Wagner, Alexander; Wang, Xue; Lopez-Conesa, Lluis; Peiró, Francesca; Rebled, José Manuel; Wehmann, Hergo-Heinrich; Daum, Winfried; Shen, Hao; Waag, Andreas
2014-02-26
3D single-crystalline, well-aligned GaN-InGaN rod arrays are fabricated by selective area growth (SAG) metal-organic vapor phase epitaxy (MOVPE) for visible-light water splitting. Epitaxial InGaN layer grows successfully on 3D GaN rods to minimize defects within the GaN-InGaN heterojunctions. The indium concentration (In ∼ 0.30 ± 0.04) is rather homogeneous in InGaN shells along the radial and longitudinal directions. The growing strategy allows us to tune the band gap of the InGaN layer in order to match the visible absorption with the solar spectrum as well as to align the semiconductor bands close to the water redox potentials to achieve high efficiency. The relation between structure, surface, and photoelectrochemical property of GaN-InGaN is explored by transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), Auger electron spectroscopy (AES), current-voltage, and open circuit potential (OCP) measurements. The epitaxial GaN-InGaN interface, pseudomorphic InGaN thin films, homogeneous and suitable indium concentration and defined surface orientation are properties demanded for systematic study and efficient photoanodes based on III-nitride heterojunctions. PMID:24517402
Structured Multifrontal Sparse Solver
2014-05-01
StruMF is an algebraic structured preconditioner for the interative solution of large sparse linear systems. The preconditioner corresponds to a multifrontal variant of sparse LU factorization in which some dense blocks of the factors are approximated with low-rank matrices. It is algebraic in that it only requires the linear system itself, and the approximation threshold that determines the accuracy of individual low-rank approximations. Favourable rank properties are obtained using a block partitioning which is amore » refinement of the partitioning induced by nested dissection ordering.« less
Sparse inpainting and isotropy
Feeney, Stephen M.; McEwen, Jason D.; Peiris, Hiranya V.; Marinucci, Domenico; Cammarota, Valentina; Wandelt, Benjamin D. E-mail: marinucc@axp.mat.uniroma2.it E-mail: h.peiris@ucl.ac.uk E-mail: cammarot@axp.mat.uniroma2.it
2014-01-01
Sparse inpainting techniques are gaining in popularity as a tool for cosmological data analysis, in particular for handling data which present masked regions and missing observations. We investigate here the relationship between sparse inpainting techniques using the spherical harmonic basis as a dictionary and the isotropy properties of cosmological maps, as for instance those arising from cosmic microwave background (CMB) experiments. In particular, we investigate the possibility that inpainted maps may exhibit anisotropies in the behaviour of higher-order angular polyspectra. We provide analytic computations and simulations of inpainted maps for a Gaussian isotropic model of CMB data, suggesting that the resulting angular trispectrum may exhibit small but non-negligible deviations from isotropy.
NASA Technical Reports Server (NTRS)
Kanerva, Pentti
1988-01-01
Theoretical models of the human brain and proposed neural-network computers are developed analytically. Chapters are devoted to the mathematical foundations, background material from computer science, the theory of idealized neurons, neurons as address decoders, and the search of memory for the best match. Consideration is given to sparse memory, distributed storage, the storage and retrieval of sequences, the construction of distributed memory, and the organization of an autonomous learning system.
Kanerva, P.
1988-01-01
Theoretical models of the human brain and proposed neural-network computers are developed analytically. Chapters are devoted to the mathematical foundations, background material from computer science, the theory of idealized neurons, neurons as address decoders, and the search of memory for the best match. Consideration is given to sparse memory, distributed storage, the storage and retrieval of sequences, the construction of distributed memory, and the organization of an autonomous learning system. 63 refs.
Sparse matrix test collections
Duff, I.
1996-12-31
This workshop will discuss plans for coordinating and developing sets of test matrices for the comparison and testing of sparse linear algebra software. We will talk of plans for the next release (Release 2) of the Harwell-Boeing Collection and recent work on improving the accessibility of this Collection and others through the World Wide Web. There will only be three talks of about 15 to 20 minutes followed by a discussion from the floor.
Mongardini, Claudio; Di Tanna, Gian Luca; Pilloni, Andrea
2014-01-01
Eradication or suppression of pathogens is a major goal in periodontal therapy. Due to the increase in antibiotic resistance, the need of new disinfection therapies is raising. Photodynamic therapy (PDT) has demonstrated anti-infective potential. No data are available on the use of light-emitting diode (LED) lights as the light source in PDT. The aim of this study was to investigate the microbiological and clinical adjunctive outcome of a new photodynamic LED device, compared to scaling and root planing in periodontitis patients in maintenance [supportive periodontal therapy (SPT)]. In this masked, split-mouth design study, 30 treated chronic periodontitis subjects (mean age, 46.2 years; 13 males) in SPT were included. Two residual interdental sites with probing pocket depth (PPD) ≥ 5 mm in two opposite quadrants, with positive bleeding on probing (BOP) and comparable periodontal breakdown, were selected. PPD, BOP and subgingival microbiological samples for real-time PCR analysis (Carpegen® PerioDiagnostics, Carpegen GmbH, Münster, Germany) were recorded at baseline and 1 week after treatment. Scaling and root planing was performed under local anesthesia. Randomly one of the sites was selected to receive adjunctive photodynamic therapy by inserting a photosensitizer (toluidine blue O solution) and exposing it to a LED light in the red spectrum (Fotosan, CMS Dental, Copenhagen, Denmark), according to the manufacturer's instructions. After 1 week, 73 % of the control sites and 27 % of the test sites were still BOP+. These differences compared to baseline values and in-between groups were statistically significantly different (p < 0.001). Mean PPD decreased from 5.47 mm (±0.68) to 4.73 mm (±0.74, p < 0.001) in control sites and from 5.63 mm (±0.85) to 4.43 mm (±1.25, p < 0.001, test vs control p = 0.01) in the test group. Microbiologically, higher reductions of relative proportions of red complex bacteria were observed in test sites (68.1 vs. 4.1 %; p = 0
Method and apparatus for distinguishing actual sparse events from sparse event false alarms
Spalding, Richard E.; Grotbeck, Carter L.
2000-01-01
Remote sensing method and apparatus wherein sparse optical events are distinguished from false events. "Ghost" images of actual optical phenomena are generated using an optical beam splitter and optics configured to direct split beams to a single sensor or segmented sensor. True optical signals are distinguished from false signals or noise based on whether the ghost image is presence or absent. The invention obviates the need for dual sensor systems to effect a false target detection capability, thus significantly reducing system complexity and cost.
and Drayton Munster, Miroslav Stoyanov
2013-09-20
Sparse Grids are the family of methods of choice for multidimensional integration and interpolation in low to moderate number of dimensions. The method is to select extend a one dimensional set of abscissas, weights and basis functions by taking a subset of all possible tensor products. The module provides the ability to create global and local approximations based on polynomials and wavelets. The software has three components, a library, a wrapper for the library that provides a command line interface via text files ad a MATLAB interface via the command line tool.
2007-04-12
The Sparse Image Format (SIF) is a file format for storing spare raster images. It works by breaking an image down into tiles. Space is savid by only storing non-uniform tiles, i.e. tiles with at least two different pixel values. If a tile is completely uniform, its common pixel value is stored instead of the complete tile raster. The software is a library in the C language used for manipulating files in SIF format. Itmore » supports large files (> 2GB) and is designed to build in Windows and Linux environments.« less
2013-09-20
Sparse Grids are the family of methods of choice for multidimensional integration and interpolation in low to moderate number of dimensions. The method is to select extend a one dimensional set of abscissas, weights and basis functions by taking a subset of all possible tensor products. The module provides the ability to create global and local approximations based on polynomials and wavelets. The software has three components, a library, a wrapper for the library thatmore » provides a command line interface via text files ad a MATLAB interface via the command line tool.« less
Eads, Damian Ryan
2007-04-12
The Sparse Image Format (SIF) is a file format for storing spare raster images. It works by breaking an image down into tiles. Space is savid by only storing non-uniform tiles, i.e. tiles with at least two different pixel values. If a tile is completely uniform, its common pixel value is stored instead of the complete tile raster. The software is a library in the C language used for manipulating files in SIF format. It supports large files (> 2GB) and is designed to build in Windows and Linux environments.
NASA Technical Reports Server (NTRS)
Denning, Peter J.
1989-01-01
Sparse distributed memory was proposed be Pentti Kanerva as a realizable architecture that could store large patterns and retrieve them based on partial matches with patterns representing current sensory inputs. This memory exhibits behaviors, both in theory and in experiment, that resemble those previously unapproached by machines - e.g., rapid recognition of faces or odors, discovery of new connections between seemingly unrelated ideas, continuation of a sequence of events when given a cue from the middle, knowing that one doesn't know, or getting stuck with an answer on the tip of one's tongue. These behaviors are now within reach of machines that can be incorporated into the computing systems of robots capable of seeing, talking, and manipulating. Kanerva's theory is a break with the Western rationalistic tradition, allowing a new interpretation of learning and cognition that respects biology and the mysteries of individual human beings.
Zhang, Lihe; Lu, Huchuan; Du, Dandan; Liu, Luning
2016-02-01
In this paper, we propose a novel tracking framework based on a sparse and discriminative hashing method. Different from the previous work, we treat object tracking as an approximate nearest neighbor searching process in a binary space. Using the hash functions, the target templates and the candidates can be projected into the Hamming space, facilitating the distance calculation and tracking efficiency. First, we integrate both the inter-class and intra-class information to train multiple hash functions for better classification, while most classifiers in previous tracking methods usually neglect the inter-class correlation, which may cause the inaccuracy. Then, we introduce sparsity into the hash coefficient vectors for dynamic feature selection, which is crucial to select the discriminative and stable features to adapt to visual variations during the tracking process. Extensive experiments on various challenging sequences show that the proposed algorithm performs favorably against the state-of-the-art methods.
Estimating sparse precision matrices
NASA Astrophysics Data System (ADS)
Padmanabhan, Nikhil; White, Martin; Zhou, Harrison H.; O'Connell, Ross
2016-08-01
We apply a method recently introduced to the statistical literature to directly estimate the precision matrix from an ensemble of samples drawn from a corresponding Gaussian distribution. Motivated by the observation that cosmological precision matrices are often approximately sparse, the method allows one to exploit this sparsity of the precision matrix to more quickly converge to an asymptotic 1/sqrt{N_sim} rate while simultaneously providing an error model for all of the terms. Such an estimate can be used as the starting point for further regularization efforts which can improve upon the 1/sqrt{N_sim} limit above, and incorporating such additional steps is straightforward within this framework. We demonstrate the technique with toy models and with an example motivated by large-scale structure two-point analysis, showing significant improvements in the rate of convergence. For the large-scale structure example, we find errors on the precision matrix which are factors of 5 smaller than for the sample precision matrix for thousands of simulations or, alternatively, convergence to the same error level with more than an order of magnitude fewer simulations.
Structural basis of photosynthetic water-splitting
Shen, Jian-Ren; Kawakami, Keisuke; Kamiya, Nobuo
2013-12-10
Photosynthetic water-splitting takes place in photosystem II (PSII), a membrane protein complex consisting of 20 subunits with an overall molecular mass of 350 kDa. The light-induced water-splitting reaction catalyzed by PSII not only converts light energy into biologically useful chemical energy, but also provides us with oxygen indispensible for sustaining oxygenic life on the earth. We have solved the structure of PSII at a 1.9 Å resolution, from which, the detailed structure of the Mn{sub 4}CaO{sub 5}-cluster, the catalytic center for water-splitting, became clear. Based on the structure of PSII at the atomic resolution, possible mechanism of light-induced water-splitting was discussed.
Howell, deceased, Louis J.
1980-01-01
Thermoelectric generator assembly accommodating differential thermal expansion between thermoelectric elements by means of a cylindrical split follower forming a slot and having internal spring loaded wedges that permit the split follower to open and close across the slot.
NASA Astrophysics Data System (ADS)
Hernandez, Svea
2012-10-01
CTE measurements are made using the "internal sparse field test", along the parallelaxis. The "POS=" optional parameter, introduced during cycle 11, is used to provideoff-center MSM positioning of some slits. All exposures are internals.
NASA Astrophysics Data System (ADS)
Wolfe, Michael
2011-10-01
CTE measurements are made using the "internal sparse field test", along the parallelaxis. The "POS=" optional parameter, introduced during cycle 11, is used to provideoff-center MSM positionings of some slits. All exposures are internals.
NASA Astrophysics Data System (ADS)
Wolfe, Michael
2010-09-01
CTE measurements are made using the "internal sparse field test", along the parallelaxis. The "POS=" optional parameter, introduced during cycle 11, is used to provideoff-center MSM positionings of some slits. All exposures are internals.
NASA Astrophysics Data System (ADS)
Hernandez, Svea
2013-10-01
CTE measurements are made using the "internal sparse field test", along the parallelaxis. The "POS=" optional parameter, introduced during cycle 11, is used to provideoff-center MSM positioning of some slits. All exposures are internals.
NASA Astrophysics Data System (ADS)
Wolfe, Michael
2009-07-01
CTE measurements are made using the "internal sparse field test", along the parallelaxis. The "POS=" optional parameter, introduced during cycle 11, is used to provideoff-center MSM positionings of some slits. All exposures are internals.
Threaded Operations on Sparse Matrices
Sneed, Brett
2015-09-01
We investigate the use of sparse matrices and OpenMP multi-threading on linear algebra operations involving them. Several sparse matrix data structures are presented. Implementation of the multi- threading primarily occurs in the level one and two BLAS functions used within the four algorithms investigated{the Power Method, Conjugate Gradient, Biconjugate Gradient, and Jacobi's Method. The bene ts of launching threads once per high level algorithm are explored.
Sparse Methods for Biomedical Data
Ye, Jieping; Liu, Jun
2013-01-01
Following recent technological revolutions, the investigation of massive biomedical data with growing scale, diversity, and complexity has taken a center stage in modern data analysis. Although complex, the underlying representations of many biomedical data are often sparse. For example, for a certain disease such as leukemia, even though humans have tens of thousands of genes, only a few genes are relevant to the disease; a gene network is sparse since a regulatory pathway involves only a small number of genes; many biomedical signals are sparse or compressible in the sense that they have concise representations when expressed in a proper basis. Therefore, finding sparse representations is fundamentally important for scientific discovery. Sparse methods based on the ℓ1 norm have attracted a great amount of research efforts in the past decade due to its sparsity-inducing property, convenient convexity, and strong theoretical guarantees. They have achieved great success in various applications such as biomarker selection, biological network construction, and magnetic resonance imaging. In this paper, we review state-of-the-art sparse methods and their applications to biomedical data. PMID:24076585
Ramadurgam, Sarath; Lin, Tzu-Ging; Yang, Chen
2014-08-13
The poor internal quantum efficiency (IQE) arising from high recombination and insufficient absorption is one of the critical challenges toward achieving high efficiency water splitting in hematite (α-Fe2O3) photoelectrodes. By combining the nanowire (NW) geometry with the localized surface plasmon resonance (LSPR) in semiconductor-metal-metal oxide core-multishell (CMS) NWs, we theoretically demonstrate an effective route to strongly improve absorption within ultrathin (sub-50 nm) hematite layers. We show that Si-Al-Fe2O3 CMS NWs exhibit photocurrent densities comparable to Si-Ag-Fe2O3 CMS and outperform Fe2O3, Si-Fe2O3 CS and Si-Au-Fe2O3 CMS NWs. Specifically; Si-Al-Fe2O3 CMS NWs reach photocurrent densities of ∼ 11.81 mA/cm(2) within a 40 nm thick hematite shell which corresponding to a solar to hydrogen (STH) efficiency of 14.5%. This corresponds to about 93% of the theoretical maximum for bulk hematite. Therefore, we establish Al as an excellent alternative plasmonic material compared to precious metals in CMS structures. Further, the absorbed photon flux is close to the NW surface in the CMS NWs, which ensures the charges generated can reach the reaction site with minimal recombining. Although the NW geometry is anisotropic, the CMS NWs exhibit polarization independent absorption over a large range of incidence angles. Finally, we show that Si-Al-Fe2O3 CMS NWs demonstrate photocurrent densities greater than ∼ 8.2 mA/cm(2) (STH efficiency of 10%) for incidence angles as large as 45°. These theoretical results strongly establish the effectiveness of the Al-based CMS NWs for achieving scalable and cost-effective photoelectrodes with improved IQE, enabling a novel route toward high efficiency water splitting.
NASA Astrophysics Data System (ADS)
Shaban, Yasser A.; Khan, Shahed U. M.
2007-10-01
Carbon modified n-type titanium oxide (CM-n-TiO 2) photoelectrodes were synthesized by thermal flame oxidation of grooved and non-grooved Ti metal sheet at several flame temperatures for different lengths of time. The photoresponse of CM-n-TiO 2 was evaluated by measuring the rate of water splitting to hydrogen and oxygen, which is proportional to observed photocurrent density. The optimized grooved CM-n-TiO 2 photoelectrodes generated photocurrent density of 11.45 mA cm -2 at applied potential of 0.242 V at illumination intensity of 100 mW cm -2 from a 150 W xenon lamp. However, under the same illumination condition the non-grooved sample generated photocurrent density of 9.17 mA cm -2 at applied potential of 0.24 V. The maximum photoconversion efficiencies obtained from wavelength dependent monochromatic photocurrents were found to be 11.16% and 8.86% for grooved and non-grooved samples, respectively, under the same illumination intensity from the xenon lamp. Importantly, for optimized grooved CM-n-TiO 2 sample, at an applied potential of 0.242 V the total conversion efficiency of 9.5% and the maximum photoconversion efficiency of 7.62% for water splitting under global air mass of 1.5 (AM 1.5) sunlight (1 sun) illuminations were observed. The carbon contents in optimized grooved and non-grooved CM-n-TiO 2 samples were found to be 19.38 at.% and 17.60 at.%, respectively, from energy dispersive analysis by X-ray (EDAX) though both samples showed same band gap energy of 2.65 eV and a mid-gap band of 1.4 eV above the valence band. The UV-Vis spectra, X-ray diffraction (XRD) spectra and scanning electron micrograms (SEM) of these samples were also given.
United States. Bonneville Power Administration.
1992-09-01
Since lighting accounts for about one-third of the energy used in commercial buildings, there is opportunity to conserve. There are two ways to reduce lighting energy use: modify lighting systems so that they used less electricity and/or reduce the number of hours the lights are used. This booklet presents a number of ways to do both. Topics covered include: reassessing lighting levels, reducing lighting levels, increasing bulb & fixture efficiency, using controls to regulate lighting, and taking advantage of daylight.
Wavelet Sparse Approximate Inverse Preconditioners
NASA Technical Reports Server (NTRS)
Chan, Tony F.; Tang, W.-P.; Wan, W. L.
1996-01-01
There is an increasing interest in using sparse approximate inverses as preconditioners for Krylov subspace iterative methods. Recent studies of Grote and Huckle and Chow and Saad also show that sparse approximate inverse preconditioner can be effective for a variety of matrices, e.g. Harwell-Boeing collections. Nonetheless a drawback is that it requires rapid decay of the inverse entries so that sparse approximate inverse is possible. However, for the class of matrices that, come from elliptic PDE problems, this assumption may not necessarily hold. Our main idea is to look for a basis, other than the standard one, such that a sparse representation of the inverse is feasible. A crucial observation is that the kind of matrices we are interested in typically have a piecewise smooth inverse. We exploit this fact, by applying wavelet techniques to construct a better sparse approximate inverse in the wavelet basis. We shall justify theoretically and numerically that our approach is effective for matrices with smooth inverse. We emphasize that in this paper we have only presented the idea of wavelet approximate inverses and demonstrated its potential but have not yet developed a highly refined and efficient algorithm.
Moniz, Savio J A; Blackman, Christopher S; Southern, Paul; Weaver, Paul M; Tang, Junwang; Carmalt, Claire J
2015-10-21
Phase-pure BiFeO3 films were grown directly via dual-source low-pressure CVD (LPCVD) from the ligand-matched precursors [Bi(O(t)Bu)3] and [Fe(O(t)Bu)3]2, without the requirement for oxidising gas or post deposition annealing. Photocatalytic testing for water oxidation revealed extremely high activity for PEC water splitting and photocatalytic water oxidation under visible light irradiation (λ > 420 nm) with a benchmark IPCE for BiFeO3 of 23% at 400 nm. The high activity is ascribed to the ultrafine morphology achieved via the LPCVD process. The performance was enhanced by over four times when the BiFeO3 photoanode is coupled to a Ni-B surface OEC.
Qian, Ling; Chen, Jian Fu; Li, Yu Hang; Wu, Long; Wang, Hai Feng; Chen, Ai Ping; Hu, P; Zheng, Li Rong; Yang, Hua Gui
2015-09-21
The efficiency of solar-energy-conversion devices depends on the absorption region and intensity of the photon collectors. Organic chromophores, which have been widely stabilized on inorganic semiconductors for light trapping, are limited by the interface between the chromophore and semiconductor. Herein we report a novel orange zinc germanate (Zn-Ge-O) with a chromophore-like structure, by which the absorption region can be dramatically expanded. Structural characterizations and theoretical calculations together reveal that the origin of visible-light response can be attributed to the unusual metallic Ge-Ge bonds which act in a similar way to organic chromophores. Benefiting from the enhanced light harvest, the orange Zn-Ge-O demonstrates superior capacity for solar-driven hydrogen production.
Yersiz, H; Cameron, A M; Carmody, I; Zimmerman, M A; Kelly, B S; Ghobrial, R M; Farmer, D G; Busuttil, R W
2006-03-01
Seventy-five thousand Americans develop organ failure each year. Fifteen percent of those on the list for transplantation die while waiting. Several possible mechanisms to expand the organ pool are being pursued including the use of extended criteria donors, living donation, and split deceased donor transplants. Cadaveric organ splitting results from improved understanding of the surgical anatomy of the liver derived from Couinaud. Early efforts focused on reduced-liver transplantation (RLT) reported by both Bismuth and Broelsch in the mid-1980s. These techniques were soon modified to create both a left lateral segment graft appropriate for a pediatric recipient and a right trisegment for an appropriately sized adult. Techniques of split liver transplantation (SLT) were also modified to create living donor liver transplantation. Pichlmayr and Bismuth reported successful split liver transplantation in 1989 and Emond reported a larger series of nine split procedures in 1990. Broelsch and Busuttil described a technical modification in which the split was performed in situ at the donor institution with surgical division completed in the heart beating cadaveric donor. In situ splitting reduces cold ischemia, simplifies identification of biliary and vascular structures, and reduces reperfusion hemorrhage. However, in situ splits require specialized skills, prolonged operating room time, and increased logistical coordination at the donor institution. At UCLA over 120 in situ splits have been performed and this technique is the default when an optimal donor is available. Split liver transplantation now accounts for 10% of adult transplantations at UCLA and 40% of pediatric transplantations.
NASA Astrophysics Data System (ADS)
2001-05-01
Third Nucleus Observed with the VLT Summary New images from the VLT show that one of the two nuclei of Comet LINEAR (C/2001 A2), now about 100 million km from the Earth, has just split into at least two pieces . The three fragments are now moving through space in nearly parallel orbits while they slowly drift apart. This comet will pass through its perihelion (nearest point to the Sun) on May 25, 2001, at a distance of about 116 million kilometres. It has brightened considerably due to the splitting of its "dirty snowball" nucleus and can now be seen with the unaided eye by observers in the southern hemisphere as a faint object in the southern constellation of Lepus (The Hare). PR Photo 18a/01 : Three nuclei of Comet LINEAR . PR Photo 18b/01 : The break-up of Comet LINEAR (false-colour). Comet LINEAR splits and brightens ESO PR Photo 18a/01 ESO PR Photo 18a/01 [Preview - JPEG: 400 x 438 pix - 55k] [Normal - JPEG: 800 x 875 pix - 136k] ESO PR Photo 18b/01 ESO PR Photo 18b/01 [Preview - JPEG: 367 x 400 pix - 112k] [Normal - JPEG: 734 x 800 pix - 272k] Caption : ESO PR Photo 18a/01 shows the three nuclei of Comet LINEAR (C/2001 A2). It is a reproduction of a 1-min exposure in red light, obtained in the early evening of May 16, 2001, with the 8.2-m VLT YEPUN (UT4) telescope at Paranal. ESO PR Photo 18b/01 shows the same image, but in a false-colour rendering for more clarity. The cometary fragment "B" (right) has split into "B1" and "B2" (separation about 1 arcsec, or 500 km) while fragment "A" (upper left) is considerably fainter. Technical information about these photos is available below. Comet LINEAR was discovered on January 3, 2001, and designated by the International Astronomical Union (IAU) as C/2001 A2 (see IAU Circular 7564 [1]). Six weeks ago, it was suddenly observed to brighten (IAUC 7605 [1]). Amateurs all over the world saw the comparatively faint comet reaching naked-eye magnitude and soon thereafter, observations with professional telescopes indicated
NASA Astrophysics Data System (ADS)
Pilipchuk, L. A.; Pilipchuk, A. S.
2015-11-01
In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure.
Pilipchuk, L. A.; Pilipchuk, A. S.
2015-11-30
In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure.
Jegerschoeld, C.V.; Virgin, I.; Styring, S. )
1990-07-03
Strong illumination of oxygen-evolving organisms inhibits the electron transport through photosystem II (photoinhibition). In addition the illumination leads to a rapid turnover of the D1 protein in the reaction center of photosystem II. In this study the light-dependent degradation of the D1 reaction center protein and the light-dependent inhibition of electron-transport reactions have been studied in thylakoid membranes in which the oxygen evolution has been reversibly inhibited by Cl- depletion. The results show that Cl(-)-depleted thylakoid membranes are very vulnerable to damage induced by illumination. Both the D1 protein and the inhibition of the oxygen evolution are 15-20 times more sensitive to illumination than in control thylakoid membranes. The presence, during the illumination, of the herbicide 3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU) prevented both the light-dependent degradation of the D1 protein and the inhibition of the electron transport. The protection exerted by DCMU is seen only in Cl(-)-depleted thylakoid membranes. These observations lead to the proposal that continuous illumination of Cl(-)-depleted thylakoid membranes generates anomalously long-lived, highly oxidizing radicals on the oxidizing side of photosystem II, which are responsible for the light-induced protein damage and inhibition. The presence of DCMU during the illumination prevents the formation of these radicals, which explains the protective effects of the herbicide. It is also observed that in Cl(-)-depleted thylakoid membranes, oxygen evolution (measured after the readdition of Cl-) is inhibited before electron transfer from diphenylcarbazide to dichlorophenolindophenol.
Fitch, Joseph P.
1999-07-06
An endoscope which reduces the volume needed by the imaging part thereof, maintains resolution of a wide diameter optical system, while increasing tool access, and allows stereographic or interferometric processing for depth and perspective information/visualization. Because the endoscope decreases the volume consumed by imaging optics such allows a larger fraction of the volume to be used for non-imaging tools, which allows smaller incisions in surgical and diagnostic medical applications thus produces less trauma to the patient or allows access to smaller volumes than is possible with larger instruments. The endoscope utilizes fiber optic light pipes in an outer layer for illumination, a multi-pupil imaging system in an inner annulus, and an access channel for other tools in the center. The endoscope is amenable to implementation as a flexible scope, and thus increases the utility thereof. Because the endoscope uses a multi-aperture pupil, it can also be utilized as an optical array, allowing stereographic and interferometric processing.
Fitch, J.P.
1999-07-06
An endoscope is disclosed which reduces the volume needed by the imaging part, maintains resolution of a wide diameter optical system, while increasing tool access, and allows stereographic or interferometric processing for depth and perspective information/visualization. Because the endoscope decreases the volume consumed by imaging optics such allows a larger fraction of the volume to be used for non-imaging tools, which allows smaller incisions in surgical and diagnostic medical applications thus produces less trauma to the patient or allows access to smaller volumes than is possible with larger instruments. The endoscope utilizes fiber optic light pipes in an outer layer for illumination, a multi-pupil imaging system in an inner annulus, and an access channel for other tools in the center. The endoscope is amenable to implementation as a flexible scope, and thus increases it's utility. Because the endoscope uses a multi-aperture pupil, it can also be utilized as an optical array, allowing stereographic and interferometric processing. 7 figs.
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
1997-07-01
CTE measurements are made using the "sparse field test", along both the serial and parallel axes. This program needs special commanding to provide {a} off-center MSM positionings of some slits, and {b} the ability to read out with any amplifier {A, B, C, or D}. All exposures are internals.
Sparse aperture mask wavefront sensor testbed results
NASA Astrophysics Data System (ADS)
Subedi, Hari; Zimmerman, Neil T.; Kasdin, N. Jeremy; Riggs, A. J. E.
2016-07-01
Coronagraphic exoplanet detection at very high contrast requires the estimation and control of low-order wave- front aberrations. At Princeton High Contrast Imaging Lab (PHCIL), we are working on a new technique that integrates a sparse-aperture mask (SAM) with a shaped pupil coronagraph (SPC) to make precise estimates of these low-order aberrations. We collect the starlight rejected from the coronagraphic image plane and interfere it using a sparse aperture mask (SAM) at the relay pupil to estimate the low-order aberrations. In our previous work we numerically demonstrated the efficacy of the technique, and proposed a method to sense and control these differential aberrations in broadband light. We also presented early testbed results in which the SAM was used to sense pointing errors. In this paper, we will briefly overview the SAM wavefront sensor technique, explain the design of the completed testbed, and report the experimental estimation results of the dominant low-order aberrations such as tip/tit, astigmatism and focus.
NASA Astrophysics Data System (ADS)
Bhirud, Ashwini P.; Sathaye, Shivaram D.; Waichal, Rupali P.; Ambekar, Jalindar D.; Park, Chan-J.; Kale, Bharat B.
2015-03-01
Highly monodispersed nitrogen doped TiO2 nanoparticles were successfully deposited on graphene (N-TiO2/Gr) by a facile in-situ wet chemical method for the first time. N-TiO2/Gr has been further used for photocatalytic hydrogen production using a naturally occurring abundant source of energy i.e. solar light. The N-TiO2/Gr nanocomposite composition was optimized by varying the concentrations of dopant nitrogen and graphene (using various concentrations of graphene) for utmost hydrogen production. The structural, optical and morphological aspects of nanocomposites were studied using XRD, UV-DRS, Raman, XPS, FESEM, and TEM. The structural study of the nanocomposite shows existence of anatase N-TiO2. Further, the details of the components present in the composition were confirmed with Raman and XPS. The morphological study shows that very tiny, 7-10 nm sized, N-TiO2 nanoparticles are deposited on the graphene sheet. The optical study reveals a drastic change in absorption edge and consequent total absorption due to nitrogen doping and presence of graphene. Considering the extended absorption edge to the visible region, these nanocomposites were further used as a photocatalyst to transform hazardous H2S waste into eco-friendly hydrogen using solar light. The N-TiO2/Gr nanocomposite with 2% graphene exhibits enhanced photocatalytic stable hydrogen production i.e. ~5941 μmol h-1 under solar light irradiation using just 0.2 gm nanocomposite, which is much higher as compared to P25, undoped TiO2 and TiO2/Gr nanocomposite. The enhancement in the photocatalytic activity is attributed to `N' doping as well as high specific surface area and charge carrier ability of graphene. The recycling of the photocatalyst shows a good stability of the nanocomposites. This work may provide new insights to design other semiconductor deposited graphene novel nanocomposites as a visible light active photocatalyst.Highly monodispersed nitrogen doped TiO2 nanoparticles were successfully
Amesos2 Templated Direct Sparse Solver Package
2011-05-24
Amesos2 is a templated direct sparse solver package. Amesos2 provides interfaces to direct sparse solvers, rather than providing native solver capabilities. Amesos2 is a derivative work of the Trilinos package Amesos.
Inverse lithography using sparse mask representations
NASA Astrophysics Data System (ADS)
Ionescu, Radu C.; Hurley, Paul; Apostol, Stefan
2015-03-01
We present a novel optimisation algorithm for inverse lithography, based on optimization of the mask derivative, a domain inherently sparse, and for rectilinear polygons, invertible. The method is first developed assuming a point light source, and then extended to general incoherent sources. What results is a fast algorithm, producing manufacturable masks (the search space is constrained to rectilinear polygons), and flexible (specific constraints such as minimal line widths can be imposed). One inherent trick is to treat polygons as continuous entities, thus making aerial image calculation extremely fast and accurate. Requirements for mask manufacturability can be integrated in the optimization without too much added complexity. We also explain how to extend the scheme for phase-changing mask optimization.
A flux-split solution procedure for unsteady flow calculations
NASA Technical Reports Server (NTRS)
Pordal, H. S.; Khosla, P. K.; Rubin, S. G.
1990-01-01
The solution of reduced Navier Stokes (RNS) equations is considered using a flux-split procedure. Unsteady flow in a two dimensional engine inlet is computed. The problems of unstart and restart are investigated. A sparse matrix direct solver combined with domain decomposition strategy is used to compute the unsteady flow field at each instant of time. Strong shock-boundary layer interaction, time varying shocks and time varying recirculation regions are efficiently captured.
Kim, Kwanghyun; Thiyagarajan, Pradheep; Ahn, Hyo-Jin; Kim, Sun-I; Jang, Ji-Hyun
2013-07-21
A gold nanoparticle-coated and surface-textured TiO2 inverse opal (Au/st-TIO) structure that provides a dramatic improvement of photoelectrochemical hydrogen generation has been fabricated by nano-patterning of TiO2 precursors on TiO2 inverse opal (TIO) and subsequent deposition of gold NPs. The surface-textured TiO2 inverse opal (st-TIO) maximizes the photon trapping effects triggered by the large dimensions of the structure while maintaining the adequate surface area achieved by the small dimensions of the structure. Au NPs are incorporated to further improve photoconversion efficiency in the visible region via surface plasmon resonance. st-TIO and Au/st-TIO exhibit a maximum photocurrent density of ∼0.58 mA cm(-2) and ∼0.8 mA cm(-2), which is 2.07 and 2.86 times higher than that of bare TIO, respectively, at an applied bias of +0.5 V versus an Ag/AgCl electrode under AM 1.5 G simulated sunlight illumination via a photocatalytic hydrogen generation reaction. The excellent performance of the surface plasmon-enhanced mesoporous st-TIO structure suggests that tailoring the nanostructure to proper dimensions, and thereby obtaining excellent light absorption, can maximize the efficiency of a variety of photoconversion devices. PMID:23733045
Moftah, Nayera Hassan; Ibrahim, Shady Mahmoud; Wahba, Nadine Hassan
2016-05-01
Acne vulgaris is an extremely common skin condition. It often leads to negative psychological consequences. Photodynamic therapy (PDT) using intense pulsed light has been introduced for effective treatment of acne. The objective was to study the effect of PDT in truncal acne vulgaris using liposomal methylene blue (LMB) versus IPL alone. Thirty-five patients with varying degrees of acne were treated with topical 0.1 % LMB hydrogel applied on the randomly selected one side of the back, and after 60 min the entire back was exposed to IPL. The procedure was done once weekly for three sessions and patients were re-evaluated 1 month after the third session by two independent dermatologists. Acne severity was graded using the Burton scale. Patient satisfaction using Cardiff Acne Disability Index (CADI) was recorded before and after treatment. On LMB-pretreated side, inflammatory acne lesion counts were significantly decreased by 56.40 % compared with 34.06 % on IPL alone. Marked improvement was seen on LMB-pretreated side in 11.5 % of patients compared with 2.8 % on IPL alone. There was a correlation between CADI score and overall improvement. Our study concluded that LMB-IPL is more effective than IPL alone, safe with tolerable pain in the treatment of acne vulgaris on the back. LMB-IPL is more effective than IPL alone, safe with tolerable pain in the treatment of acne vulgaris on the back.
Kim, Kwanghyun; Thiyagarajan, Pradheep; Ahn, Hyo-Jin; Kim, Sun-I; Jang, Ji-Hyun
2013-07-21
A gold nanoparticle-coated and surface-textured TiO2 inverse opal (Au/st-TIO) structure that provides a dramatic improvement of photoelectrochemical hydrogen generation has been fabricated by nano-patterning of TiO2 precursors on TiO2 inverse opal (TIO) and subsequent deposition of gold NPs. The surface-textured TiO2 inverse opal (st-TIO) maximizes the photon trapping effects triggered by the large dimensions of the structure while maintaining the adequate surface area achieved by the small dimensions of the structure. Au NPs are incorporated to further improve photoconversion efficiency in the visible region via surface plasmon resonance. st-TIO and Au/st-TIO exhibit a maximum photocurrent density of ∼0.58 mA cm(-2) and ∼0.8 mA cm(-2), which is 2.07 and 2.86 times higher than that of bare TIO, respectively, at an applied bias of +0.5 V versus an Ag/AgCl electrode under AM 1.5 G simulated sunlight illumination via a photocatalytic hydrogen generation reaction. The excellent performance of the surface plasmon-enhanced mesoporous st-TIO structure suggests that tailoring the nanostructure to proper dimensions, and thereby obtaining excellent light absorption, can maximize the efficiency of a variety of photoconversion devices.
Fast sparse matrix-vector multiplication by exploiting variable block structure
Vuduc, R W; Moon, H
2005-07-07
We improve the performance of sparse matrix-vector multiply (SpMV) on modern cache-based superscalar machines when the matrix structure consists of multiple, irregularly aligned rectangular blocks. Matrices from finite element modeling applications often have this kind of structure. Our technique splits the matrix, A, into a sum, A{sub 1} + A{sub 2} + ... + A{sub s}, where each term is stored in a new data structure, unaligned block compressed sparse row (UBCSR) format . The classical alternative approach of storing A in a block compressed sparse row (BCSR) format yields limited performance gains because it imposes a particular alignment of the matrix non-zero structure, leading to extra work from explicitly padded zeros. Combining splitting and UBCSR reduces this extra work while retaining the generally lower memory bandwidth requirements and register-level tiling opportunities of BCSR. Using application test matrices, we show empirically that speedups can be as high as 2.1x over not blocking at all, and as high as 1.8x over the standard BCSR implementation used in prior work. When performance does not improve, split UBCSR can still significantly reduce matrix storage. Through extensive experiments, we further show that the empirically optimal number of splittings s and the block size for each matrix term A{sub i} will in practice depend on the matrix and hardware platform. Our data lay a foundation for future development of fully automated methods for tuning these parameters.
Tablet Splitting: A Risky Practice
... and splitting tablets in an effort to save money. Regarding the practice of splitting tablets, the Food ... tablet. So a patient may try to save money by buying the 30 mg tablets and splitting ...
Turner, H.
1996-12-31
This paper presents mathematical results that can sometimes be used to simplify the task of reasoning about a default theory, by {open_quotes}splitting it into parts.{close_quotes} These so-called Splitting Theorems for default logic are related in spirit to {open_quotes}partial evaluation{close_quotes} in logic programming, in which results obtained from one part of a program are used to simplify the remainder of the program. In this paper we focus primarily on the statement and proof of the Splitting Theorems for default logic. We illustrate the usefulness of the results by applying them to an example default theory for commonsense reasoning about action.
Finding communities in sparse networks
NASA Astrophysics Data System (ADS)
Singh, Abhinav; Humphries, Mark D.
2015-03-01
Spectral algorithms based on matrix representations of networks are often used to detect communities, but classic spectral methods based on the adjacency matrix and its variants fail in sparse networks. New spectral methods based on non-backtracking random walks have recently been introduced that successfully detect communities in many sparse networks. However, the spectrum of non-backtracking random walks ignores hanging trees in networks that can contain information about their community structure. We introduce the reluctant backtracking operators that explicitly account for hanging trees as they admit a small probability of returning to the immediately previous node, unlike the non-backtracking operators that forbid an immediate return. We show that the reluctant backtracking operators can detect communities in certain sparse networks where the non-backtracking operators cannot, while performing comparably on benchmark stochastic block model networks and real world networks. We also show that the spectrum of the reluctant backtracking operator approximately optimises the standard modularity function. Interestingly, for this family of non- and reluctant-backtracking operators the main determinant of performance on real-world networks is whether or not they are normalised to conserve probability at each node.
Highly parallel sparse Cholesky factorization
NASA Technical Reports Server (NTRS)
Gilbert, John R.; Schreiber, Robert
1990-01-01
Several fine grained parallel algorithms were developed and compared to compute the Cholesky factorization of a sparse matrix. The experimental implementations are on the Connection Machine, a distributed memory SIMD machine whose programming model conceptually supplies one processor per data element. In contrast to special purpose algorithms in which the matrix structure conforms to the connection structure of the machine, the focus is on matrices with arbitrary sparsity structure. The most promising algorithm is one whose inner loop performs several dense factorizations simultaneously on a 2-D grid of processors. Virtually any massively parallel dense factorization algorithm can be used as the key subroutine. The sparse code attains execution rates comparable to those of the dense subroutine. Although at present architectural limitations prevent the dense factorization from realizing its potential efficiency, it is concluded that a regular data parallel architecture can be used efficiently to solve arbitrarily structured sparse problems. A performance model is also presented and it is used to analyze the algorithms.
Sparse Matrices in MATLAB: Design and Implementation
NASA Technical Reports Server (NTRS)
Gilbert, John R.; Moler, Cleve; Schreiber, Robert
1992-01-01
The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations. The only change to the outward appearance of the MATLAB language is a pair of commands to create full or sparse matrices. Nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user. The sparse data structure represents a matrix in space proportional to the number of nonzero entries, and most of the operations compute sparse results in time proportional to the number of arithmetic operations on nonzeros.
NASA Technical Reports Server (NTRS)
Stapleton, Thomas J. (Inventor)
2015-01-01
A concentric split flow filter may be configured to remove odor and/or bacteria from pumped air used to collect urine and fecal waste products. For instance, filter may be designed to effectively fill the volume that was previously considered wasted surrounding the transport tube of a waste management system. The concentric split flow filter may be configured to split the air flow, with substantially half of the air flow to be treated traveling through a first bed of filter media and substantially the other half of the air flow to be treated traveling through the second bed of filter media. This split flow design reduces the air velocity by 50%. In this way, the pressure drop of filter may be reduced by as much as a factor of 4 as compare to the conventional design.
NASA Technical Reports Server (NTRS)
Klein, J. A.; Murray, C. D.; Stein, J. A.
1971-01-01
Tool accurately splits glass tubing so cuts are aligned 180 deg apart and reassembled tube forms low pressure, gastight enclosure. Device should interest industries using cylindrical closed glass containers.
Hayter, J P; Vaughan, E D; Brown, J S
1996-10-01
Both upper and lower lip splits, usually with osteotomy of the underlying jaw, improve access to the deep structures of the head and neck. A simple modification to the midline lip split is to incorporate a chevron in both the peri-oral skin and vermilion margin. The advantages are: accurate wound closure, no straight line contracture and a broken line of the peri-oral scar. This improves the aesthetic result of the healed lip.
Polarized Antenna Splitting Functions
Larkoski, Andrew J.; Peskin, Michael E.; /SLAC
2009-10-17
We consider parton showers based on radiation from QCD dipoles or 'antennae'. These showers are built from 2 {yields} 3 parton splitting processes. The question then arises of what functions replace the Altarelli-Parisi splitting functions in this approach. We give a detailed answer to this question, applicable to antenna showers in which partons carry definite helicity, and to both initial- and final-state emissions.
NASA Astrophysics Data System (ADS)
Wang, Ruosong; Xu, Xiaoxue; Zhang, Yi; Chang, Zhimin; Sun, Zaicheng; Dong, Wen-Fei
2015-06-01
We have designed a novel semiconductor core/layer nanostructure of a uniform ZnO@TiO2 nanorod array modified with a ZnIn0.25Cu0.02S1.395 solid-solution on the surface via a facile hydrothermal synthesis. This novel nanostructure combines the merits of all components and meets the requirements of photovoltaic system application. An intimate PN heterojunction is formed from the ZnO@TiO2 nanorod and polymetallic sulphide solid-solution, which is remarkably beneficial for the effective visible light absorption and rapid charge carrier separation. The nanostructures exhibit higher photocurrent and incident photon to electron conversion efficiency (IPCE) under no bias potential versus the Ag/AgCl electrode. We also analyzed the interface and photoelectrochemical characteristics of the nanostructure and revealed the kinetic process of the electron and hole transmission. In addition, the photoanode test shows the hydrogen production capability of the nanostructures from solar water splitting. These results verified that the ZnO and TiO2 can be sensitized by the polymetallic sulfide for UV-Vis light driven energy conversion. Importantly, the approach we used to design the photoanode enables the development of micro-nano electronic devices with enhanced performance.We have designed a novel semiconductor core/layer nanostructure of a uniform ZnO@TiO2 nanorod array modified with a ZnIn0.25Cu0.02S1.395 solid-solution on the surface via a facile hydrothermal synthesis. This novel nanostructure combines the merits of all components and meets the requirements of photovoltaic system application. An intimate PN heterojunction is formed from the ZnO@TiO2 nanorod and polymetallic sulphide solid-solution, which is remarkably beneficial for the effective visible light absorption and rapid charge carrier separation. The nanostructures exhibit higher photocurrent and incident photon to electron conversion efficiency (IPCE) under no bias potential versus the Ag/AgCl electrode. We also
Robust Sparse Blind Source Separation
NASA Astrophysics Data System (ADS)
Chenot, Cecile; Bobin, Jerome; Rapin, Jeremy
2015-11-01
Blind Source Separation is a widely used technique to analyze multichannel data. In many real-world applications, its results can be significantly hampered by the presence of unknown outliers. In this paper, a novel algorithm coined rGMCA (robust Generalized Morphological Component Analysis) is introduced to retrieve sparse sources in the presence of outliers. It explicitly estimates the sources, the mixing matrix, and the outliers. It also takes advantage of the estimation of the outliers to further implement a weighting scheme, which provides a highly robust separation procedure. Numerical experiments demonstrate the efficiency of rGMCA to estimate the mixing matrix in comparison with standard BSS techniques.
Isospin Splittings of Doubly Heavy Baryons
Brodsky, Stanley J.; Guo, Feng-Kun; Hanhart, Christoph; Meissner, Ulf-G.; /Julich, Forschungszentrum /JCHP, Julich /IAS, Julich /Bonn U., HISKP /Bonn U.
2011-08-18
The SELEX Collaboration has reported a very large isospin splitting of doubly charmed baryons. We show that this effect would imply that the doubly charmed baryons are very compact. One intriguing possibility is that such baryons have a linear geometry Q-q-Q where the light quark q oscillates between the two heavy quarks Q, analogous to a linear molecule such as carbon dioxide. However, using conventional arguments, the size of a heavy-light hadron is expected to be around 0.5 fm, much larger than the size needed to explain the observed large isospin splitting. Assuming the distance between two heavy quarks is much smaller than that between the light quark and a heavy one, the doubly heavy baryons are related to the heavy mesons via heavy quark-diquark symmetry. Based on this symmetry, we predict the isospin splittings for doubly heavy baryons including {Xi}{sub cc}, {Xi}{sub bb} and {Xi}{sub bc}. The prediction for the {Xi}{sub cc} is much smaller than the SELEX value. On the other hand, the {Xi}{sub bb} baryons are predicted to have an isospin splitting as large as (6.3 {+-} 1.7) MeV. An experimental study of doubly bottomed baryons is therefore very important to better understand the structure of baryons with heavy quarks.
Gene Golub; Kwok Ko
2009-03-30
The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.
Overall water splitting on (oxy)nitride photocatalysts
NASA Astrophysics Data System (ADS)
Domen, Kazunari
2008-08-01
Overall water splitting to form hydrogen and oxygen on a heterogeneous photocatalyst using solar energy is an attractive process for large-scale hydrogen production. In recent years, numerous attempts have been made for the development of visible-light-responsive photocatalysts to efficiently utilize solar energy. In this article, recent research progress in the development of visible-light-driven photocatalysts is described, specifically focusing on our efforts made on the development of (oxy)nitride photocatalysts for overall water splitting.
NASA Technical Reports Server (NTRS)
1981-01-01
The development of a stablized Zeeman split laser for use in a polarization profilometer is discussed. A Hewlett-Packard laser was modified to stabilize the Zeeman split beat frequency thereby increasing the phase measurement accuracy from the Hewlett-Packard 3 degrees to an accuracy of .01 degrees. The addition of a two layered inductive winding converts the laser to a current controlled oscillator whose frequency is linearly related to coil current. This linear relationship between coil current and laser frequency permits phase locking the laser frequency to a stable crystal controlled reference frequency. The stability of the system is examined and the equipment operation procedures are outlined.
Image fusion using sparse overcomplete feature dictionaries
Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt
2015-10-06
Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.
ERIC Educational Resources Information Center
Wilkins, Jesse L. M.; Norton, Anderson
2011-01-01
Teaching experiments have generated several hypotheses concerning the construction of fraction schemes and operations and relationships among them. In particular, researchers have hypothesized that children's construction of splitting operations is crucial to their construction of more advanced fractions concepts (Steffe, 2002). The authors…
Veligdan, James T.
2007-05-29
A video image is displayed from an optical panel by splitting the image into a plurality of image components, and then projecting the image components through corresponding portions of the panel to collectively form the image. Depth of the display is correspondingly reduced.
Veligdan, James T.
2005-05-31
A video image is displayed from an optical panel by splitting the image into a plurality of image components, and then projecting the image components through corresponding portions of the panel to collectively form the image. Depth of the display is correspondingly reduced.
ERIC Educational Resources Information Center
Norton, Anderson; Wilkins, Jesse L. M.
2012-01-01
Piagetian theory describes mathematical development as the construction and organization of mental operations within psychological structures. Research on student learning has identified the vital roles of two particular operations--splitting and units coordination--play in students' development of advanced fractions knowledge. Whereas Steffe and…
Plasmonic solar water splitting.
Warren, S. C.; Thimsen, E.
2012-01-01
The study of the optoelectronic effects of plasmonic metal nanoparticles on semiconductors has led to compelling evidence for plasmon-enhanced water splitting. We review the relevant physics, device geometries, and research progress in this area. We focus on localized surface plasmons and their effects on semiconductors, particularly in terms of energy transfer, scattering, and hot electron transfer.
Pan, Chengsi; Takata, Tsuyoshi; Domen, Kazunari
2016-01-26
One of the main targets of studies on water splitting photocatalysts is to develop semiconductor materials with narrower bandgaps capable of overall water splitting for efficient harvesting of solar energy. A series of transition-metal oxynitrides, LaMgx Ta1-xO1+3xN2-3x(x ≥ 1/3), with a complex perovskite structure was reported as the first example of overall water splitting operable at up to 600 nm. The photocatalytic behavior of LaMg1/3Ta2/3O2N was investigated in detail in order to optimize photocatalyst preparation and water-splitting activity. Various attempts exploring photocatalyst preparation steps, that is, cocatalyst selection, coating material and method, and synthesis method for the oxide precursor, revealed photocatalyst structures necessary for achieving overall water splitting. Careful examination of photocatalyst preparation procedures likely enhanced the quality of the produced photocatalyst, leading to a more homogeneous coating quality and semiconductor particles with fewer defects. Thus, the photocatalytic activity for water splitting on LaMg1/3Ta2/3O2N was largely enhanced.
Sparse representation for the ISAR image reconstruction
NASA Astrophysics Data System (ADS)
Hu, Mengqi; Montalbo, John; Li, Shuxia; Sun, Ligang; Qiao, Zhijun G.
2016-05-01
In this paper, a sparse representation of the data for an inverse synthetic aperture radar (ISAR) system is provided in two dimensions. The proposed sparse representation motivates the use a of a Convex Optimization that recovers the image with far less samples, which is required by Nyquist-Shannon sampling theorem to increases the efficiency and decrease the cost of calculation in radar imaging.
Sparse Modeling for Astronomical Data Analysis
NASA Astrophysics Data System (ADS)
Ikeda, Shiro; Odaka, Hirokazu; Uemura, Makoto
2016-03-01
For astronomical data analysis, there have been proposed multiple methods based on sparse modeling. We have proposed a method for Compton camera imaging. The proposed approach is a sparse modeling method, but the derived algorithm is different from LASSO. We explain the problem and how we derived the method.
Framelet-Based Sparse Unmixing of Hyperspectral Images.
Zhang, Guixu; Xu, Yingying; Fang, Faming
2016-04-01
Spectral unmixing aims at estimating the proportions (abundances) of pure spectrums (endmembers) in each mixed pixel of hyperspectral data. Recently, a semi-supervised approach, which takes the spectral library as prior knowledge, has been attracting much attention in unmixing. In this paper, we propose a new semi-supervised unmixing model, termed framelet-based sparse unmixing (FSU), which promotes the abundance sparsity in framelet domain and discriminates the approximation and detail components of hyperspectral data after framelet decomposition. Due to the advantages of the framelet representations, e.g., images have good sparse approximations in framelet domain, and most of the additive noises are included in the detail coefficients, the FSU model has a better antinoise capability, and accordingly leads to more desirable unmixing performance. The existence and uniqueness of the minimizer of the FSU model are then discussed, and the split Bregman algorithm and its convergence property are presented to obtain the minimal solution. Experimental results on both simulated data and real data demonstrate that the FSU model generally performs better than the compared methods. PMID:26849863
Approximate inverse preconditioners for general sparse matrices
Chow, E.; Saad, Y.
1994-12-31
Preconditioned Krylov subspace methods are often very efficient in solving sparse linear matrices that arise from the discretization of elliptic partial differential equations. However, for general sparse indifinite matrices, the usual ILU preconditioners fail, often because of the fact that the resulting factors L and U give rise to unstable forward and backward sweeps. In such cases, alternative preconditioners based on approximate inverses may be attractive. We are currently developing a number of such preconditioners based on iterating on each column to get the approximate inverse. For this approach to be efficient, the iteration must be done in sparse mode, i.e., we must use sparse-matrix by sparse-vector type operatoins. We will discuss a few options and compare their performance on standard problems from the Harwell-Boeing collection.
Maximum constrained sparse coding for image representation
NASA Astrophysics Data System (ADS)
Zhang, Jie; Zhao, Danpei; Jiang, Zhiguo
2015-12-01
Sparse coding exhibits good performance in many computer vision applications by finding bases which capture highlevel semantics of the data and learning sparse coefficients in terms of the bases. However, due to the fact that bases are non-orthogonal, sparse coding can hardly preserve the samples' similarity, which is important for discrimination. In this paper, a new image representing method called maximum constrained sparse coding (MCSC) is proposed. Sparse representation with more active coefficients means more similarity information, and the infinite norm is added to the solution for this purpose. We solve the optimizer by constraining the codes' maximum and releasing the residual to other dictionary atoms. Experimental results on image clustering show that our method can preserve the similarity of adjacent samples and maintain the sparsity of code simultaneously.
Large-scale sparse singular value computations
NASA Technical Reports Server (NTRS)
Berry, Michael W.
1992-01-01
Four numerical methods for computing the singular value decomposition (SVD) of large sparse matrices on a multiprocessor architecture are presented. Lanczos and subspace iteration-based methods for determining several of the largest singular triplets (singular values and corresponding left and right-singular vectors) for sparse matrices arising from two practical applications: information retrieval and seismic reflection tomography are emphasized. The target architectures for implementations are the CRAY-2S/4-128 and Alliant FX/80. The sparse SVD problem is well motivated by recent information-retrieval techniques in which dominant singular values and their corresponding singular vectors of large sparse term-document matrices are desired, and by nonlinear inverse problems from seismic tomography applications which require approximate pseudo-inverses of large sparse Jacobian matrices.
Artificial photosynthesis for solar water-splitting
NASA Astrophysics Data System (ADS)
Tachibana, Yasuhiro; Vayssieres, Lionel; Durrant, James R.
2012-08-01
Hydrogen generated from solar-driven water-splitting has the potential to be a clean, sustainable and abundant energy source. Inspired by natural photosynthesis, artificial solar water-splitting devices are now being designed and tested. Recent developments based on molecular and/or nanostructure designs have led to advances in our understanding of light-induced charge separation and subsequent catalytic water oxidation and reduction reactions. Here we review some of the recent progress towards developing artificial photosynthetic devices, together with their analogies to biological photosynthesis, including technologies that focus on the development of visible-light active hetero-nanostructures and require an understanding of the underlying interfacial carrier dynamics. Finally, we propose a vision for a future sustainable hydrogen fuel community based on artificial photosynthesis.
Frantz, C.E.; Cawley, W.E.
1961-05-01
A tool is described for cutting a coolant tube adapted to contain fuel elements to enable the tube to be removed from a graphite moderator mass. The tool splits the tube longitudinally into halves and curls the longitudinal edges of the halves inwardly so that they occupy less space and can be moved radially inwardly away from the walls of the hole in the graphite for easy removal from the graphite.
Audin, L.
1994-12-31
EPAct covers a vast territory beyond lighting and, like all legislation, also contains numerous {open_quotes}favors,{close_quotes} compromises, and even some sleight-of-hand. Tucked away under Title XIX, for example, is an increase from 20% to 28% tax on gambling winnings, effective January 1, 1993 - apparently as a way to help pay for new spending listed elsewhere in the bill. Overall, it is a landmark piece of legislation, about a decade overdue. It remains to be seen how the Federal Government will enforce upgrading of state (or even their own) energy codes. There is no mention of funding for {open_quotes}energy police{close_quotes} in EPAct. Merely creating such a national standard, however, provides a target for those who sincerely wish to create an energy-efficient future.
Atom beams split by gentle persuasion
Pool, R.
1994-02-25
Two different research teams have taken a big step toward atom interferometry. They have succeeded in splitting atomic beams by using atoms in spin states that neither absorb nor reemit laser light. By proper adjustment of experimental conditions, atoms are changed from one spin state to another, without passing through the intermediary excited state. The atoms in essence absorb momentum from the laser photons, without absorption or emission of photons. The change in momentum deflects atoms in the proper spin state.
Photosynthetic water splitting for hydrogen fuel synthesis
NASA Astrophysics Data System (ADS)
Greenbaum, E.
Three key advances in photosynthesis research are reported. A significant advance in microalgal water splitting has been made. In the linear, low-intensity region of the light saturation curves, equivalent solar conversion efficiencies of 10% have been measured. A technological advance in the ability to genetically screen individual algal colonies has been made. Successive subcultures of anaerobiosis-stressed Chlamydomonas reinhardtii exhibited enhanced capacity for photoproduction of hydrogen and oxygen.
Reflection hologram solar spectrum-splitting filters
NASA Astrophysics Data System (ADS)
Zhang, Deming; Gordon, Michael; Russo, Juan M.; Vorndran, Shelby; Escarra, Matthew; Atwater, Harry; Kostuk, Raymond K.
2012-10-01
In this paper we investigate the use of holographic filters in solar spectrum splitting applications. Photovoltaic (PV) systems utilizing spectrum splitting have higher theoretical conversion efficiency than single bandgap cell modules. Dichroic band-rejection filters have been used for spectrum splitting applications with some success however these filters are limited to spectral control at fixed reflection angles. Reflection holographic filters are fabricated by recording interference pattern of two coherent beams at arbitrary construction angles. This feature can be used to control the angles over which spectral selectivity is obtained. In addition focusing wavefronts can also be used to increase functionality in the filter. Holograms fabricated in dichromated gelatin (DCG) have the benefit of light weight, low scattering and absorption losses. In addition, reflection holograms recorded in the Lippmann configuration have been shown to produce strong chirping as a result of wet processing. Chirping broadens the filter rejection bandwidth both spectrally and angularly. It can be tuned to achieve spectral bandwidth suitable for spectrum splitting applications. We explore different DCG film fabrication and processing parameters to improve the optical performance of the filter. The diffraction efficiency bandwidth and scattering losses are optimized by changing the exposure energy, isopropanol dehydration bath temperature and hardening bath duration. A holographic spectrum-splitting PV module is proposed with Gallium Arsenide (GaAs) and silicon (Si) PV cells with efficiency of 25.1% and 19.7% respectively. The calculated conversion efficiency with a prototype hologram is 27.94% which is 93.94% compared to the ideal spectrum-splitting efficiency of 29.74%.
Efficient nearest neighbors via robust sparse hashing.
Cherian, Anoop; Sra, Suvrit; Morellas, Vassilios; Papanikolopoulos, Nikolaos
2014-08-01
This paper presents a new nearest neighbor (NN) retrieval framework: robust sparse hashing (RSH). Our approach is inspired by the success of dictionary learning for sparse coding. Our key idea is to sparse code the data using a learned dictionary, and then to generate hash codes out of these sparse codes for accurate and fast NN retrieval. But, direct application of sparse coding to NN retrieval poses a technical difficulty: when data are noisy or uncertain (which is the case with most real-world data sets), for a query point, an exact match of the hash code generated from the sparse code seldom happens, thereby breaking the NN retrieval. Borrowing ideas from robust optimization theory, we circumvent this difficulty via our novel robust dictionary learning and sparse coding framework called RSH, by learning dictionaries on the robustified counterparts of the perturbed data points. The algorithm is applied to NN retrieval on both simulated and real-world data. Our results demonstrate that RSH holds significant promise for efficient NN retrieval against the state of the art.
Sparse High Dimensional Models in Economics.
Fan, Jianqing; Lv, Jinchi; Qi, Lei
2011-09-01
This paper reviews the literature on sparse high dimensional models and discusses some applications in economics and finance. Recent developments of theory, methods, and implementations in penalized least squares and penalized likelihood methods are highlighted. These variable selection methods are proved to be effective in high dimensional sparse modeling. The limits of dimensionality that regularization methods can handle, the role of penalty functions, and their statistical properties are detailed. Some recent advances in ultra-high dimensional sparse modeling are also briefly discussed. PMID:22022635
Sparse High Dimensional Models in Economics
Fan, Jianqing; Lv, Jinchi; Qi, Lei
2010-01-01
This paper reviews the literature on sparse high dimensional models and discusses some applications in economics and finance. Recent developments of theory, methods, and implementations in penalized least squares and penalized likelihood methods are highlighted. These variable selection methods are proved to be effective in high dimensional sparse modeling. The limits of dimensionality that regularization methods can handle, the role of penalty functions, and their statistical properties are detailed. Some recent advances in ultra-high dimensional sparse modeling are also briefly discussed. PMID:22022635
Enhancing Scalability of Sparse Direct Methods
Li, Xiaoye S.; Demmel, James; Grigori, Laura; Gu, Ming; Xia,Jianlin; Jardin, Steve; Sovinec, Carl; Lee, Lie-Quan
2007-07-23
TOPS is providing high-performance, scalable sparse direct solvers, which have had significant impacts on the SciDAC applications, including fusion simulation (CEMM), accelerator modeling (COMPASS), as well as many other mission-critical applications in DOE and elsewhere. Our recent developments have been focusing on new techniques to overcome scalability bottleneck of direct methods, in both time and memory. These include parallelizing symbolic analysis phase and developing linear-complexity sparse factorization methods. The new techniques will make sparse direct methods more widely usable in large 3D simulations on highly-parallel petascale computers.
Stereotypes, stepmothers, and splitting.
Radomisli, M
1981-01-01
Asserting that preteen children cannot tolerate ambivalence, a recent study extols the "wicked stepmother" stereotype in fairy tales for providing a safe outlet for child-mother aggression. However, even theories which consider splitting normal in object-relations development see it as operating mostly before age 3. Dualistic thinking is not ubiquitous in childhood, nor is it ever outgrown. Rather, it is a mode of organizing experience mythopoetically; we learn to minimize its intrusions in dealings with day-to-day realities. There is no scientific justification for (and there are moral objections to) the propagation of the wicked stepmother stereotype.
On finding supernodes for sparse matrix computations
Liu, J.W.H. . Dept. of Computer Science); Ng, E.; Peyton, B.W. )
1990-06-01
A simple characterization of fundamental supernodes is given in terms of the row subtrees of sparse Cholesky factors in the elimination tree. Using this characterization, we present an efficient algorithm that determines the set of such supernodes in time proportional to the number of nonzeros and equations in the original matrix. Experimental results are included to demonstrate the use of this algorithm in the context of sparse supernodal symbolic factorization. 18 refs., 3 figs., 3 tabs.
Recent advances in semiconductors for photocatalytic and photoelectrochemical water splitting.
Hisatomi, Takashi; Kubota, Jun; Domen, Kazunari
2014-11-21
Photocatalytic and photoelectrochemical water splitting under irradiation by sunlight has received much attention for production of renewable hydrogen from water on a large scale. Many challenges still remain in improving energy conversion efficiency, such as utilizing longer-wavelength photons for hydrogen production, enhancing the reaction efficiency at any given wavelength, and increasing the lifetime of the semiconductor materials. This introductory review covers the fundamental aspects of photocatalytic and photoelectrochemical water splitting. Controlling the semiconducting properties of photocatalysts and photoelectrode materials is the primary concern in developing materials for solar water splitting, because they determine how much photoexcitation occurs in a semiconductor under solar illumination and how many photoexcited carriers reach the surface where water splitting takes place. Given a specific semiconductor material, surface modifications are important not only to activate the semiconductor for water splitting but also to facilitate charge separation and to upgrade the stability of the material under photoexcitation. In addition, reducing resistance loss and forming p-n junction have a significant impact on the efficiency of photoelectrochemical water splitting. Correct evaluation of the photocatalytic and photoelectrochemical activity for water splitting is becoming more important in enabling an accurate comparison of a number of studies based on different systems. In the latter part, recent advances in the water splitting reaction under visible light will be presented with a focus on non-oxide semiconductor materials to give an overview of the various problems and solutions.
Sparse extreme learning machine for classification.
Bai, Zuo; Huang, Guang-Bin; Wang, Danwei; Wang, Han; Westover, M Brandon
2014-10-01
Extreme learning machine (ELM) was initially proposed for single-hidden-layer feedforward neural networks (SLFNs). In the hidden layer (feature mapping), nodes are randomly generated independently of training data. Furthermore, a unified ELM was proposed, providing a single framework to simplify and unify different learning methods, such as SLFNs, least square support vector machines, proximal support vector machines, and so on. However, the solution of unified ELM is dense, and thus, usually plenty of storage space and testing time are required for large-scale applications. In this paper, a sparse ELM is proposed as an alternative solution for classification, reducing storage space and testing time. In addition, unified ELM obtains the solution by matrix inversion, whose computational complexity is between quadratic and cubic with respect to the training size. It still requires plenty of training time for large-scale problems, even though it is much faster than many other traditional methods. In this paper, an efficient training algorithm is specifically developed for sparse ELM. The quadratic programming problem involved in sparse ELM is divided into a series of smallest possible sub-problems, each of which are solved analytically. Compared with SVM, sparse ELM obtains better generalization performance with much faster training speed. Compared with unified ELM, sparse ELM achieves similar generalization performance for binary classification applications, and when dealing with large-scale binary classification problems, sparse ELM realizes even faster training speed than unified ELM. PMID:25222727
Visual tracking via robust multitask sparse prototypes
NASA Astrophysics Data System (ADS)
Zhang, Huanlong; Hu, Shiqiang; Yu, Junyang
2015-03-01
Sparse representation has been applied to an online subspace learning-based tracking problem. To handle partial occlusion effectively, some researchers introduce l1 regularization to principal component analysis (PCA) reconstruction. However, in these traditional tracking methods, the representation of each object observation is often viewed as an individual task so the inter-relationship between PCA basis vectors is ignored. We propose a new online visual tracking algorithm with multitask sparse prototypes, which combines multitask sparse learning with PCA-based subspace representation. We first extend a visual tracking algorithm with sparse prototypes in multitask learning framework to mine inter-relations between subtasks. Then, to avoid the problem that enforcing all subtasks to share the same structure may result in degraded tracking results, we impose group sparse constraints on the coefficients of PCA basis vectors and element-wise sparse constraints on the error coefficients, respectively. Finally, we show that the proposed optimization problem can be effectively solved using the accelerated proximal gradient method with the fast convergence. Experimental results compared with the state-of-the-art tracking methods demonstrate that the proposed algorithm achieves favorable performance when the object undergoes partial occlusion, motion blur, and illumination changes.
Learning discriminative dictionary for group sparse representation.
Sun, Yubao; Liu, Qingshan; Tang, Jinhui; Tao, Dacheng
2014-09-01
In recent years, sparse representation has been widely used in object recognition applications. How to learn the dictionary is a key issue to sparse representation. A popular method is to use l1 norm as the sparsity measurement of representation coefficients for dictionary learning. However, the l1 norm treats each atom in the dictionary independently, so the learned dictionary cannot well capture the multisubspaces structural information of the data. In addition, the learned subdictionary for each class usually shares some common atoms, which weakens the discriminative ability of the reconstruction error of each subdictionary. This paper presents a new dictionary learning model to improve sparse representation for image classification, which targets at learning a class-specific subdictionary for each class and a common subdictionary shared by all classes. The model is composed of a discriminative fidelity, a weighted group sparse constraint, and a subdictionary incoherence term. The discriminative fidelity encourages each class-specific subdictionary to sparsely represent the samples in the corresponding class. The weighted group sparse constraint term aims at capturing the structural information of the data. The subdictionary incoherence term is to make all subdictionaries independent as much as possible. Because the common subdictionary represents features shared by all classes, we only use the reconstruction error of each class-specific subdictionary for classification. Extensive experiments are conducted on several public image databases, and the experimental results demonstrate the power of the proposed method, compared with the state-of-the-arts.
Robust face recognition via sparse representation.
Wright, John; Yang, Allen Y; Ganesh, Arvind; Sastry, S Shankar; Ma, Yi
2009-02-01
We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the recognition problem as one of classifying among multiple linear regression models and argue that new theory from sparse signal representation offers the key to addressing this problem. Based on a sparse representation computed by l{1}-minimization, we propose a general classification algorithm for (image-based) object recognition. This new framework provides new insights into two crucial issues in face recognition: feature extraction and robustness to occlusion. For feature extraction, we show that if sparsity in the recognition problem is properly harnessed, the choice of features is no longer critical. What is critical, however, is whether the number of features is sufficiently large and whether the sparse representation is correctly computed. Unconventional features such as downsampled images and random projections perform just as well as conventional features such as Eigenfaces and Laplacianfaces, as long as the dimension of the feature space surpasses certain threshold, predicted by the theory of sparse representation. This framework can handle errors due to occlusion and corruption uniformly by exploiting the fact that these errors are often sparse with respect to the standard (pixel) basis. The theory of sparse representation helps predict how much occlusion the recognition algorithm can handle and how to choose the training images to maximize robustness to occlusion. We conduct extensive experiments on publicly available databases to verify the efficacy of the proposed algorithm and corroborate the above claims.
Ueno, Kosei; Oshikiri, Tomoya; Misawa, Hiroaki
2016-01-18
Visible- and near-infrared-light-driven water splitting, which splits water molecules to generate hydrogen and oxygen gases, is a significant subject in artificial photosynthesis with the goal of achieving a low-carbon society. In recent years, considerable attention has been paid to studies on the development of a plasmon-induced water-splitting system responding to visible light. In this review, we categorized water-splitting systems as gold-nanoparticle-loaded semiconductor photocatalytic particles system and metallic-nanoparticles-loaded semiconductor photoelectrode systems, and introduce the latest studies according to these categories. Especially, we describe the studies that optimize a material or a structural design of metallic-nanoparticle-loaded semiconductor photoelectrodes and consider a whole water-splitting system, including a cathode design. Furthermore, we discuss important points when studying plasmon-induced water splitting, and we describe a methodology that enhances plasmon-induced water-splitting efficiency.
Alsbjoern, B.F.S.; Sorensen, B.
1986-12-01
Extensively burned patients suffer from lack of sufficient autologous donor skin. Meshing and wide expansion of the obtained split skin has met the requirement to a large degree. However, the wider the expansion, the less chance of a proper take. By covering widely expanded autografts with viable cadaver split skin, the take has been improved. If the epidermal Langerhans cells in the cadaver split skin are depressed by ultraviolet B light and glucocorticosteroids before grafting, a prolonged allograft take can be achieved and the healing of the underlying autografts is ensured for an extended period. Grafting results in 6 patients with extensive burns are reported.
New shape models of asteroids reconstructed from sparse-in-time photometry
NASA Astrophysics Data System (ADS)
Durech, Josef; Hanus, Josef; Vanco, Radim; Oszkiewicz, Dagmara Anna
2015-08-01
Asteroid physical parameters - the shape, the sidereal rotation period, and the spin axis orientation - can be reconstructed from the disk-integrated photometry either dense (classical lightcurves) or sparse in time by the lightcurve inversion method. We will review our recent progress in asteroid shape reconstruction from sparse photometry. The problem of finding a unique solution of the inverse problem is time consuming because the sidereal rotation period has to be found by scanning a wide interval of possible periods. This can be efficiently solved by splitting the period parameter space into small parts that are sent to computers of volunteers and processed in parallel. We will show how this approach of distributed computing works with currently available sparse photometry processed in the framework of project Asteroids@home. In particular, we will show the results based on the Lowell Photometric Database. The method produce reliable asteroid models with very low rate of false solutions and the pipelines and codes can be directly used also to other sources of sparse photometry - Gaia data, for example. We will present the distribution of spin axis of hundreds of asteroids, discuss the dependence of the spin obliquity on the size of an asteroid,and show examples of spin-axis distribution in asteroid families that confirm the Yarkovsky/YORP evolution scenario.
Balanced Sparse Model for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
Liu, Yunsong; Cai, Jian-Feng; Zhan, Zhifang; Guo, Di; Ye, Jing; Chen, Zhong; Qu, Xiaobo
2015-01-01
Compressed sensing has shown to be promising to accelerate magnetic resonance imaging. In this new technology, magnetic resonance images are usually reconstructed by enforcing its sparsity in sparse image reconstruction models, including both synthesis and analysis models. The synthesis model assumes that an image is a sparse combination of atom signals while the analysis model assumes that an image is sparse after the application of an analysis operator. Balanced model is a new sparse model that bridges analysis and synthesis models by introducing a penalty term on the distance of frame coefficients to the range of the analysis operator. In this paper, we study the performance of the balanced model in tight frame based compressed sensing magnetic resonance imaging and propose a new efficient numerical algorithm to solve the optimization problem. By tuning the balancing parameter, the new model achieves solutions of three models. It is found that the balanced model has a comparable performance with the analysis model. Besides, both of them achieve better results than the synthesis model no matter what value the balancing parameter is. Experiment shows that our proposed numerical algorithm constrained split augmented Lagrangian shrinkage algorithm for balanced model (C-SALSA-B) converges faster than previously proposed algorithms accelerated proximal algorithm (APG) and alternating directional method of multipliers for balanced model (ADMM-B). PMID:25849209
Baryogenesis through split Higgsogenesis
NASA Astrophysics Data System (ADS)
Davidson, Sacha; Felipe, Ricardo González; Serôdio, Hugo; Silva, João P.
2013-11-01
We study the cosmological evolution of asymmetries in the two-Higgs doublet extension of the Standard Model, prior to the electroweak phase transition. If Higgs flavour-exchanging interactions are sufficiently slow, then a relative asymmetry among the Higgs doublets corresponds to an effectively conserved quantum number. Since the magnitude of the Higgs couplings depends on the choice of basis in the Higgs doublet space, we attempt to formulate basis-independent out-of-equilibrium conditions. We show that an initial asymmetry between the Higgs scalars, which could be generated by CP violation in the Higgs sector, will be transformed into a baryon asymmetry by the sphalerons, without the need of B - L violation. This novel mechanism of baryogenesis through (split) Higgsogenesis is exemplified with simple scenarios based on the out-of-equilibrium decay of heavy singlet scalar fields into the Higgs doublets.
Leptogenesis from split fermions
Nagatani, Yukinori; Perez, Gilad
2004-01-11
We present a new type of leptogenesis mechanism based on a two-scalar split-fermions framework. At high temperatures the bulk scalar vacuum expectation values (VEVs) vanish and lepton number is strongly violated. Below some temperature, T{sub c}, the scalars develop extra dimension dependent VEVs. This transition is assumed to proceed via a first order phase transition. In the broken phase the fermions are localized and lepton number violation is negligible. The lepton-bulk scalar Yukawa couplings contain sizable CP phases which induce lepton production near the interface between the two phases. We provide a qualitative estimation of the resultant baryon asymmetry which agrees with current observation. The neutrino flavor parameters are accounted for by the above model with an additional approximate U(1) symmetry.
Chen, Shanshan; Qi, Yu; Hisatomi, Takashi; Ding, Qian; Asai, Tomohiro; Li, Zheng; Ma, Su Su Khine; Zhang, Fuxiang; Domen, Kazunari; Li, Can
2015-07-13
An (oxy)nitride-based heterostructure for powdered Z-scheme overall water splitting is presented. Compared with the single MgTa2O(6-x)N(y) or TaON photocatalyst, a MgTa2O(6-x)N(y)/TaON heterostructure fabricated by a simple one-pot nitridation route was demonstrated to effectively suppress the recombination of carriers by efficient spatial charge separation and decreased defect density. By employing Pt-loaded MgTa2O(6-x)N(y)/TaON as a H2-evolving photocatalyst, a Z-scheme overall water splitting system with an apparent quantum efficiency (AQE) of 6.8% at 420 nm was constructed (PtO(x)-WO3 and IO3(-)/I(-) pairs were used as an O2-evolving photocatalyst and a redox mediator, respectively), the activity of which is circa 7 or 360 times of that using Pt-TaON or Pt-MgTa2O(6-x)N)y) as a H2-evolving photocatalyst, respectively. To the best of our knowledge, this is the highest AQE among the powdered Z-scheme overall water splitting systems ever reported. PMID:26037473
Chen, Shanshan; Qi, Yu; Hisatomi, Takashi; Ding, Qian; Asai, Tomohiro; Li, Zheng; Ma, Su Su Khine; Zhang, Fuxiang; Domen, Kazunari; Li, Can
2015-07-13
An (oxy)nitride-based heterostructure for powdered Z-scheme overall water splitting is presented. Compared with the single MgTa2O(6-x)N(y) or TaON photocatalyst, a MgTa2O(6-x)N(y)/TaON heterostructure fabricated by a simple one-pot nitridation route was demonstrated to effectively suppress the recombination of carriers by efficient spatial charge separation and decreased defect density. By employing Pt-loaded MgTa2O(6-x)N(y)/TaON as a H2-evolving photocatalyst, a Z-scheme overall water splitting system with an apparent quantum efficiency (AQE) of 6.8% at 420 nm was constructed (PtO(x)-WO3 and IO3(-)/I(-) pairs were used as an O2-evolving photocatalyst and a redox mediator, respectively), the activity of which is circa 7 or 360 times of that using Pt-TaON or Pt-MgTa2O(6-x)N)y) as a H2-evolving photocatalyst, respectively. To the best of our knowledge, this is the highest AQE among the powdered Z-scheme overall water splitting systems ever reported.
Process for photosynthetically splitting water
Greenbaum, E.
1982-01-28
In one form of the invention, hydrogen is produced by providing a reactor containing a body of water. The water contains photolytic material, i.e., photoactive material containing a hydrogen-catalyst. The interior of the reactor is isolated from atmosphere and includes a volume for receiving gases evolved from the body of water. The photolytic material is exposed to light to effect photosynthetic splitting of the water into gaseous hydrogen and oxygen. The gas-receiving volume is continuously evacuated by pumping to promote evolution of gaseous hydrogen and oxygen into that volume and to withdraw them therefrom. In another form of the invention, separation of the hydrogen and oxygen is effected by selectively diffusing the hydrogen through a heated semipermeable membrane in a separation zone while maintaining across the zone a magnetic field gradient biasing the oxygen away from the membrane. In a third form of the invention, the withdrawn gas is contacted with a membrane blocking flow of water vapor to the region for effecting recovery of the hydrogen. In a fourth embodiment, the invention comprises a process for selectively recovering hydrogen from a gas mixture comprising hydrogen and oxygen. The process is conducted in a separation zone and comprises contacting the mixture with a semipermeable membrane effecting selective diffusion of hydrogen while maintaining across the zone a magnetic field gradient effecting movement of oxygen in a direction away from the membrane.
Hydrogen productivity by photosynthetic water splitting
Greenbaum, E.
1990-01-01
This paper reviews recent progress in the field of hydrogen production by photosynthetic water splitting for both in vitro and in vivo systems. Absolute thermodynamic efficiencies of conversion of light energy into energy of molecular hydrogen by intact microalgae have been measured with an original physical measuring technique using a tin-oxide semiconducting gas sensor. Thin films of microalgae comprising 5-20 cellular monolayers have been entrapped on filter paper, thereby constraining them in a well-defined circular geometry. Based on absolute light absorption of visible polychromatic illumination in the low-intensity region of the light saturation curve, conversion efficiencies of 6 to 24% have been obtained. These values are the highest ever measured for hydrogen evolution by green algae. 34 refs., 7 figs., 1 tab.
Fast wavelet based sparse approximate inverse preconditioner
Wan, W.L.
1996-12-31
Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.
Sparse regularization for force identification using dictionaries
NASA Astrophysics Data System (ADS)
Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng
2016-04-01
The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.
Photosynthetic water splitting
NASA Astrophysics Data System (ADS)
Greenbaum, E.
It has been demonstrated that eukaryotic green algae (as represented by Chlamydomonas) are inherently rugged algae with respect to the biophotolysis of water. There also exists a potential for selecting subpropulations of wild-type algae with enhanced properties for hydrogen and oxygen production. Second, hydrogenase activity in macroscopic marine algae does not conform to the conventional dogma of the catalog of reactions that this enzyme is supposed to catalyze. A kinetic argument has been presented which suggests that, with respect to light activated reactions, hydrogenase in these organisms operates primarily in a hydrogen uptake mode. Third, the light saturation curves for the simultaneous photoproduction of hydrogen and oxygen do not have the same analytical shape. It is suggested that a Photosystem I-like hydrogen producing light reaction may be present in anaerobically adapted Scenedesmus which is uncoupled from the Z scheme.
Renewable hydrogen production by photosynthetic water splitting
Greenbaum, E.; Lee, J.W.
1998-06-01
This mission-oriented research project is focused on the production of renewable hydrogen. The authors have demonstrated that certain unicellular green algae are capable of sustained simultaneous photoproduction of hydrogen and oxygen by light-activated photosynthetic water splitting. It is the goal of this project to develop a practical chemical engineering system for the development of an economic process that can be used to produce renewable hydrogen. There are several fundamental problems that need to be solved before the application of this scientific knowledge can be applied to the development a practical process: (I) maximizing net thermodynamic conversion efficiency of light energy into hydrogen energy, (2) development of oxygen-sensitive hydrogenase-containing mutants, and (3) development of bioreactors that can be used in a real-world chemical engineering process. The authors are addressing each of these problems here at ORNL and in collaboration with their research colleagues at the National Renewable Energy Laboratory, the University of California, Berkeley, and the University of Hawaii. This year the authors have focused on item 1 above. In particular, they have focused on the question of how many light reactions are required to split water to molecular hydrogen and oxygen.
Tensor methods for large, sparse unconstrained optimization
Bouaricha, A.
1996-11-01
Tensor methods for unconstrained optimization were first introduced by Schnabel and Chow [SIAM J. Optimization, 1 (1991), pp. 293-315], who describe these methods for small to moderate size problems. This paper extends these methods to large, sparse unconstrained optimization problems. This requires an entirely new way of solving the tensor model that makes the methods suitable for solving large, sparse optimization problems efficiently. We present test results for sets of problems where the Hessian at the minimizer is nonsingular and where it is singular. These results show that tensor methods are significantly more efficient and more reliable than standard methods based on Newton`s method.
Analog system for computing sparse codes
Rozell, Christopher John; Johnson, Don Herrick; Baraniuk, Richard Gordon; Olshausen, Bruno A.; Ortman, Robert Lowell
2010-08-24
A parallel dynamical system for computing sparse representations of data, i.e., where the data can be fully represented in terms of a small number of non-zero code elements, and for reconstructing compressively sensed images. The system is based on the principles of thresholding and local competition that solves a family of sparse approximation problems corresponding to various sparsity metrics. The system utilizes Locally Competitive Algorithms (LCAs), nodes in a population continually compete with neighboring units using (usually one-way) lateral inhibition to calculate coefficients representing an input in an over complete dictionary.
Multisnapshot Sparse Bayesian Learning for DOA
NASA Astrophysics Data System (ADS)
Gerstoft, Peter; Mecklenbrauker, Christoph F.; Xenaki, Angeliki; Nannuru, Santosh
2016-10-01
The directions of arrival (DOA) of plane waves are estimated from multi-snapshot sensor array data using Sparse Bayesian Learning (SBL). The prior source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters the unknown variances (i.e. the source powers). For a complex Gaussian likelihood with hyperparameter the unknown noise variance, the corresponding Gaussian posterior distribution is derived. For a given number of DOAs, the hyperparameters are automatically selected by maximizing the evidence and promote sparse DOA estimates. The SBL scheme for DOA estimation is discussed and evaluated competitively against LASSO ($\\ell_1$-regularization), conventional beamforming, and MUSIC
Efficient quantum circuits for arbitrary sparse unitaries
Jordan, Stephen P.; Wocjan, Pawel
2009-12-15
Arbitrary exponentially large unitaries cannot be implemented efficiently by quantum circuits. However, we show that quantum circuits can efficiently implement any unitary provided it has at most polynomially many nonzero entries in any row or column, and these entries are efficiently computable. One can formulate a model of computation based on the composition of sparse unitaries which includes the quantum Turing machine model, the quantum circuit model, anyonic models, permutational quantum computation, and discrete time quantum walks as special cases. Thus, we obtain a simple unified proof that these models are all contained in BQP. Furthermore, our general method for implementing sparse unitaries simplifies several existing quantum algorithms.
Sparse Density Estimation on the Multinomial Manifold.
Hong, Xia; Gao, Junbin; Chen, Sheng; Zia, Tanveer
2015-11-01
A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion for the finite mixture model. Since the constraint on the mixing coefficients of the finite mixture model is on the multinomial manifold, we use the well-known Riemannian trust-region (RTR) algorithm for solving this problem. The first- and second-order Riemannian geometry of the multinomial manifold are derived and utilized in the RTR algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with an accuracy competitive with those of existing kernel density estimators. PMID:25647665
Resonant Nanophotonic Spectrum Splitting for Ultrathin Multijunction Solar Cells
2015-01-01
We present an approach to spectrum splitting for photovoltaics that utilizes the resonant optical properties of nanostructures for simultaneous voltage enhancement and spatial separation of different colors of light. Using metal–insulator–metal resonators commonly used in broadband metamaterial absorbers we show theoretically that output voltages can be enhanced significantly compared to single-junction devices. However, the approach is general and works for any type of resonator with a large absorption cross section. Due to its resonant nature, the spectrum splitting occurs within only a fraction of the wavelength, as opposed to traditional spectrum splitting methods, where many wavelengths are required. Combining nanophotonic spectrum splitting with other nanophotonic approaches to voltage enhancements, such as angle restriction and concentration, may lead to highly efficient but deeply subwavelength photovoltaic devices. PMID:26322319
Measuring and Evaluating TCP Splitting for Cloud Services
NASA Astrophysics Data System (ADS)
Pathak, Abhinav; Wang, Y. Angela; Huang, Cheng; Greenberg, Albert; Hu, Y. Charlie; Kern, Randy; Li, Jin; Ross, Keith W.
In this paper, we examine the benefits of split-TCP proxies, deployed in an operational world-wide network, for accelerating cloud services. We consider a fraction of a network consisting of a large number of satellite datacenters, which host split-TCP proxies, and a smaller number of mega datacenters, which ultimately perform computation or provide storage. Using web search as an exemplary case study, our detailed measurements reveal that a vanilla TCP splitting solution deployed at the satellite DCs reduces the 95 th percentile of latency by as much as 43% when compared to serving queries directly from the mega DCs. Through careful dissection of the measurement results, we characterize how individual components, including proxy stacks, network protocols, packet losses and network load, can impact the latency. Finally, we shed light on further optimizations that can fully realize the potential of the TCP splitting solution.
Split supersymmetry radiates flavor
NASA Astrophysics Data System (ADS)
Baumgart, Matthew; Stolarski, Daniel; Zorawski, Thomas
2014-09-01
Radiative flavor models where the hierarchies of Standard Model (SM) fermion masses and mixings are explained via loop corrections are elegant ways to solve the SM flavor puzzle. Here we build such a model in the context of mini-split supersymmetry (SUSY) where both flavor and SUSY breaking occur at a scale of 1000 TeV. This model is consistent with the observed Higgs mass, unification, and dark matter as a weakly interacting massive particle. The high scale allows large flavor mixing among the sfermions, which provides part of the mechanism for radiative flavor generation. In the deep UV, all flavors are treated democratically, but at the SUSY-breaking scale, the third, second, and first generation Yukawa couplings are generated at tree level, one loop, and two loops, respectively. Save for one, all the dimensionless parameters in the theory are O(1), with the exception being a modest and technically natural tuning that explains both the smallness of the bottom Yukawa coupling and the largeness of the Cabibbo angle.
Split Hubbard bands at low densities
NASA Astrophysics Data System (ADS)
Hansen, Daniel; Perepelitsky, Edward; Shastry, B. Sriram
2011-05-01
We present a numerical scheme for the Hubbard model that throws light on the rather esoteric nature of the upper and lower Hubbard bands, which have been invoked often in literature. We present a self-consistent solution of the ladder-diagram equations for the Hubbard model, and show that these provide, at least in the limit of low densities of particles, a vivid picture of the Hubbard split bands. We also address the currently topical problem of decay of the doublon states that are measured in optical trap studies, using both the ladder scheme and also an exact two-particle calculation of a relevant Green’s function.
Infrared image recognition based on structure sparse and atomic sparse parallel
NASA Astrophysics Data System (ADS)
Wu, Yalu; Li, Ruilong; Xu, Yi; Wang, Liping
2015-12-01
Use the redundancy of the super complete dictionary can capture the structural features of the image effectively, can achieving the effective representation of the image. However, the commonly used atomic sparse representation without regard the structure of the dictionary and the unrelated non-zero-term in the process of the computation, though structure sparse consider the structure feature of dictionary, the majority coefficients of the blocks maybe are non-zero, it may affect the identification efficiency. For the disadvantages of these two sparse expressions, a weighted parallel atomic sparse and sparse structure is proposed, and the recognition efficiency is improved by the adaptive computation of the optimal weights. The atomic sparse expression and structure sparse expression are respectively, and the optimal weights are calculated by the adaptive method. Methods are as follows: training by using the less part of the identification sample, the recognition rate is calculated by the increase of the certain step size and t the constraint between weight. The recognition rate as the Z axis, two weight values respectively as X, Y axis, the resulting points can be connected in a straight line in the 3 dimensional coordinate system, by solving the highest recognition rate, the optimal weights can be obtained. Through simulation experiments can be known, the optimal weights based on adaptive method are better in the recognition rate, weights obtained by adaptive computation of a few samples, suitable for parallel recognition calculation, can effectively improve the recognition rate of infrared images.
Second SIAM conference on sparse matrices: Abstracts. Final technical report
1996-12-31
This report contains abstracts on the following topics: invited and long presentations (IP1 & LP1); sparse matrix reordering & graph theory I; sparse matrix tools & environments I; eigenvalue computations I; iterative methods & acceleration techniques I; applications I; parallel algorithms I; sparse matrix reordering & graphy theory II; sparse matrix tool & environments II; least squares & optimization I; iterative methods & acceleration techniques II; applications II; eigenvalue computations II; least squares & optimization II; parallel algorithms II; sparse direct methods; iterative methods & acceleration techniques III; eigenvalue computations III; and sparse matrix reordering & graph theory III.
Facial expression recognition with facial parts based sparse representation classifier
NASA Astrophysics Data System (ADS)
Zhi, Ruicong; Ruan, Qiuqi
2009-10-01
Facial expressions play important role in human communication. The understanding of facial expression is a basic requirement in the development of next generation human computer interaction systems. Researches show that the intrinsic facial features always hide in low dimensional facial subspaces. This paper presents facial parts based facial expression recognition system with sparse representation classifier. Sparse representation classifier exploits sparse representation to select face features and classify facial expressions. The sparse solution is obtained by solving l1 -norm minimization problem with constraint of linear combination equation. Experimental results show that sparse representation is efficient for facial expression recognition and sparse representation classifier obtain much higher recognition accuracies than other compared methods.
Split-illumination electron holography
Tanigaki, Toshiaki; Aizawa, Shinji; Suzuki, Takahiro; Park, Hyun Soon; Inada, Yoshikatsu; Matsuda, Tsuyoshi; Taniyama, Akira; Shindo, Daisuke; Tonomura, Akira
2012-07-23
We developed a split-illumination electron holography that uses an electron biprism in the illuminating system and two biprisms (applicable to one biprism) in the imaging system, enabling holographic interference micrographs of regions far from the sample edge to be obtained. Using a condenser biprism, we split an electron wave into two coherent electron waves: one wave is to illuminate an observation area far from the sample edge in the sample plane and the other wave to pass through a vacuum space outside the sample. The split-illumination holography has the potential to greatly expand the breadth of applications of electron holography.
Apparatus Splits Glass Tubes Longitudinally
NASA Technical Reports Server (NTRS)
Shaw, Ernest; Manahan, Robert O'neil
1993-01-01
Tubes split into half cylinders by hot-wire/thermal-shock method. Tube to be cut placed on notched jig in apparatus. Nichrome wire stretched between arms of pivoted carriage and oriented parallel to notch. Wire heated by electrical current while resting on tube. After heating for about 1 minute for each millimeter of thickness of glass, tube quenched in water and split by resulting thermal shock. Apparatus used to split tubes in sizes ranging from 3/8 in. in diameter by 1 in. long to 1 1/2 in. in diameter by 4 in. long.
Learning Stable Multilevel Dictionaries for Sparse Representations.
Thiagarajan, Jayaraman J; Ramamurthy, Karthikeyan Natesan; Spanias, Andreas
2015-09-01
Sparse representations using learned dictionaries are being increasingly used with success in several data processing and machine learning applications. The increasing need for learning sparse models in large-scale applications motivates the development of efficient, robust, and provably good dictionary learning algorithms. Algorithmic stability and generalizability are desirable characteristics for dictionary learning algorithms that aim to build global dictionaries, which can efficiently model any test data similar to the training samples. In this paper, we propose an algorithm to learn dictionaries for sparse representations from large scale data, and prove that the proposed learning algorithm is stable and generalizable asymptotically. The algorithm employs a 1-D subspace clustering procedure, the K-hyperline clustering, to learn a hierarchical dictionary with multiple levels. We also propose an information-theoretic scheme to estimate the number of atoms needed in each level of learning and develop an ensemble approach to learn robust dictionaries. Using the proposed dictionaries, the sparse code for novel test data can be computed using a low-complexity pursuit procedure. We demonstrate the stability and generalization characteristics of the proposed algorithm using simulations. We also evaluate the utility of the multilevel dictionaries in compressed recovery and subspace learning applications.
Multilevel sparse functional principal component analysis.
Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S
2014-01-29
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions. PMID:24872597
Multilevel sparse functional principal component analysis
Di, Chongzhi; Crainiceanu, Ciprian M.; Jank, Wolfgang S.
2014-01-01
We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions. PMID:24872597
Algorithms for sparse nonnegative Tucker decompositions.
Mørup, Morten; Hansen, Lars Kai; Arnfred, Sidse M
2008-08-01
There is a increasing interest in analysis of large-scale multiway data. The concept of multiway data refers to arrays of data with more than two dimensions, that is, taking the form of tensors. To analyze such data, decomposition techniques are widely used. The two most common decompositions for tensors are the Tucker model and the more restricted PARAFAC model. Both models can be viewed as generalizations of the regular factor analysis to data of more than two modalities. Nonnegative matrix factorization (NMF), in conjunction with sparse coding, has recently been given much attention due to its part-based and easy interpretable representation. While NMF has been extended to the PARAFAC model, no such attempt has been done to extend NMF to the Tucker model. However, if the tensor data analyzed are nonnegative, it may well be relevant to consider purely additive (i.e., nonnegative) Tucker decompositions). To reduce ambiguities of this type of decomposition, we develop updates that can impose sparseness in any combination of modalities, hence, proposed algorithms for sparse nonnegative Tucker decompositions (SN-TUCKER). We demonstrate how the proposed algorithms are superior to existing algorithms for Tucker decompositions when the data and interactions can be considered nonnegative. We further illustrate how sparse coding can help identify what model (PARAFAC or Tucker) is more appropriate for the data as well as to select the number of components by turning off excess components. The algorithms for SN-TUCKER can be downloaded from Mørup (2007).
Self-Control in Sparsely Coded Networks
NASA Astrophysics Data System (ADS)
Dominguez, D. R. C.; Bollé, D.
1998-03-01
A complete self-control mechanism is proposed in the dynamics of neural networks through the introduction of a time-dependent threshold, determined in function of both the noise and the pattern activity in the network. Especially for sparsely coded models this mechanism is shown to considerably improve the storage capacity, the basins of attraction, and the mutual information content.
Sparse matrix orderings for factorized inverse preconditioners
Benzi, M.; Tuama, M.
1998-09-01
The effect of reorderings on the performance of factorized sparse approximate inverse preconditioners is considered. It is shown that certain reorderings can be very beneficial both in the preconditioner construction phase and in terms of the rate of convergence of the preconditioned iteration.
STIS Sparse Field CTE test {Cycle 9}
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
2000-07-01
CTE measurements are made using the "sparse field test", along both the serial and parallel axes. This program needs special commanding to provide {a} off-center MSM positionings of some slits, and {b} the ability to read out with any amplifier {A, B, C, or D}. All exposures are internals.
STIS Sparse Field CTE test {Cycle 8}
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
1999-07-01
CTE measurements are made using the "sparse field test", along both the serial and parallel axes. This program needs special commanding to provide {a} off-center MSM positionings of some slits, and {b} the ability to read out with any amplifier {A, B, C, or D}. All exposures are internals.
NASA Astrophysics Data System (ADS)
Ottiger, Philipp; Leutwyler, Samuel; Köppel, Horst
2012-05-01
The S1/S2 state exciton splittings of symmetric doubly hydrogen-bonded gas-phase dimers provide spectroscopic benchmarks for the excited-state electronic couplings between UV chromophores. These have important implications for electronic energy transfer in multichromophoric systems ranging from photosynthetic light-harvesting antennae to photosynthetic reaction centers, conjugated polymers, molecular crystals, and nucleic acids. We provide laser spectroscopic data on the S1/S2 excitonic splitting Δexp of the doubly H-bonded o-cyanophenol (oCP) dimer and compare to the splittings of the dimers of (2-aminopyridine)2, [(2AP)2], (2-pyridone)2, [(2PY)2], (benzoic acid)2, [(BZA)2], and (benzonitrile)2, [(BN)2]. The experimental S1/S2 excitonic splittings are Δexp = 16.4 cm-1 for (oCP)2, 11.5 cm-1 for (2AP)2, 43.5 cm-1 for (2PY)2, and <1 cm-1 for (BZA)2. In contrast, the vertical S1/S2 energy gaps Δcalc calculated by the approximate second-order coupled cluster (CC2) method for the same dimers are 10-40 times larger than the Δexp values. The qualitative failure of this and other ab initio methods to reproduce the exciton splitting Δexp arises from the Born-Oppenheimer (BO) approximation, which implicitly assumes the strong-coupling case and cannot be employed to evaluate excitonic splittings of systems that are in the weak-coupling limit. Given typical H-bond distances and oscillator strengths, the majority of H-bonded dimers lie in the weak-coupling limit. In this case, the monomer electronic-vibrational coupling upon electronic excitation must be accounted for; the excitonic splittings arise between the vibronic (and not the electronic) transitions. The discrepancy between the BO-based splittings Δcalc and the much smaller experimental Δexp values is resolved by taking into account the quenching of the BO splitting by the intramolecular vibronic coupling in the monomer S1 ← S0 excitation. The vibrational quenching factors Γ for the five dimers (oCP)2, (2AP)2
Perfectly correlated phase screen realization using sparse spectrum harmonic augmentation.
Naeh, Itay; Katzir, Abraham
2014-09-20
The split-step Fourier method is commonly used to simulate the propagation of radiation in a turbulent atmosphere using two-dimensional phase screens that have the desired spatial spectral content given by the atmospheric power spectrum. Using existing methodologies, isotropy of the structure function can never be achieved, mainly along the axis of propagation, for several reasons. In this paper, we introduce the sparse spectrum harmonic augmentation method that will address the lack of isotropy along the propagation axis, the limited achievable frequencies, and the limited time development possible using known approaches. Following the methodology described will produce phase screens that are transversely endless, perfectly correlated along the propagation axis, and contain the desired spectral content, including the low frequencies that even though they contain most of the energy, are usually neglected. The methodology presented can be used for many aspects of wave propagation in random media, such as atmospheric propagation, underwater acoustics, radio wave propagation in the ionosphere, and more. PMID:25322093
Chiral Extrapolation of Lattice Data for Heavy Meson Hyperfine Splittings
X.-H. Guo; P.C. Tandy; A.W. Thomas
2006-03-01
We investigate the chiral extrapolation of the lattice data for the light-heavy meson hyperfine splittings D*-D and B*-B to the physical region for the light quark mass. The chiral loop corrections providing non-analytic behavior in m{sub {pi}} are consistent with chiral perturbation theory for heavy mesons. Since chiral loop corrections tend to decrease the already too low splittings obtained from linear extrapolation, we investigate two models to guide the form of the analytic background behavior: the constituent quark potential model, and the covariant model of QCD based on the ladder-rainbow truncation of the Dyson-Schwinger equations. The extrapolated hyperfine splittings remain clearly below the experimental values even allowing for the model dependence in the description of the analytic background.
Harris, Karen; Ferguson, Janice; Hills, Samantha
2014-04-01
Twenty-five women, referred for hair removal by electrolysis, were enrolled in a split face study to treat facial hirsutism. Each patient was treated on six occasions: one-half of the face with electrolysis and the other side with an intense pulsed light source. Patients were evaluated with respect to reduction in hair counts, side effects and discomfort during treatment. Re-growth was assessed at 3, 6 and 9 months following treatment. All patients, except one with very sparse, fair hair growth, preferred treatment with the Intense Pulsed Light and rated their average hair reduction with this method as 77% after five treatments. The overall patient satisfaction rates as determined by visual analogue scales were 8.3 out of 10 for IPL and 5.4 out of 10 for electrolysis.
Semantic Parameters of Split Intransitivity.
ERIC Educational Resources Information Center
Van Valin, Jr., Robert D.
1990-01-01
This paper argues that split-intransitive phenomena are better explained in semantic terms. A semantic analysis is carried out in Role and Reference Grammar, which assumes the theory of verb classification proposed in Dowty 1979. (49 references) (JL)
Su, Hai; Xing, Fuyong; Yang, Lin
2016-06-01
Successful diagnostic and prognostic stratification, treatment outcome prediction, and therapy planning depend on reproducible and accurate pathology analysis. Computer aided diagnosis (CAD) is a useful tool to help doctors make better decisions in cancer diagnosis and treatment. Accurate cell detection is often an essential prerequisite for subsequent cellular analysis. The major challenge of robust brain tumor nuclei/cell detection is to handle significant variations in cell appearance and to split touching cells. In this paper, we present an automatic cell detection framework using sparse reconstruction and adaptive dictionary learning. The main contributions of our method are: 1) A sparse reconstruction based approach to split touching cells; 2) An adaptive dictionary learning method used to handle cell appearance variations. The proposed method has been extensively tested on a data set with more than 2000 cells extracted from 32 whole slide scanned images. The automatic cell detection results are compared with the manually annotated ground truth and other state-of-the-art cell detection algorithms. The proposed method achieves the best cell detection accuracy with a F1 score = 0.96.
Entropy Splitting and Numerical Dissipation
NASA Technical Reports Server (NTRS)
Yee, H. C.; Vinokur, M.; Djomehri, M. J.
1999-01-01
A rigorous stability estimate for arbitrary order of accuracy of spatial central difference schemes for initial-boundary value problems of nonlinear symmetrizable systems of hyperbolic conservation laws was established recently by Olsson and Oliger (1994) and Olsson (1995) and was applied to the two-dimensional compressible Euler equations for a perfect gas by Gerritsen and Olsson (1996) and Gerritsen (1996). The basic building block in developing the stability estimate is a generalized energy approach based on a special splitting of the flux derivative via a convex entropy function and certain homogeneous properties. Due to some of the unique properties of the compressible Euler equations for a perfect gas, the splitting resulted in the sum of a conservative portion and a non-conservative portion of the flux derivative. hereafter referred to as the "Entropy Splitting." There are several potential desirable attributes and side benefits of the entropy splitting for the compressible Euler equations that were not fully explored in Gerritsen and Olsson. The paper has several objectives. The first is to investigate the choice of the arbitrary parameter that determines the amount of splitting and its dependence on the type of physics of current interest to computational fluid dynamics. The second is to investigate in what manner the splitting affects the nonlinear stability of the central schemes for long time integrations of unsteady flows such as in nonlinear aeroacoustics and turbulence dynamics. If numerical dissipation indeed is needed to stabilize the central scheme, can the splitting help minimize the numerical dissipation compared to its un-split cousin? Extensive numerical study on the vortex preservation capability of the splitting in conjunction with central schemes for long time integrations will be presented. The third is to study the effect of the non-conservative proportion of splitting in obtaining the correct shock location for high speed complex shock
Sparse representations and convex optimization as tools for LOFAR radio interferometric imaging
NASA Astrophysics Data System (ADS)
Girard, J. N.; Garsden, H.; Starck, J. L.; Corbel, S.; Woiselle, A.; Tasse, C.; McKean, J. P.; Bobin, J.
2015-08-01
Compressed sensing theory is slowly making its way to solve more and more astronomical inverse problems. We address here the application of sparse representations, convex optimization and proximal theory to radio interferometric imaging. First, we expose the theory behind interferometric imaging, sparse representations and convex optimization, and second, we illustrate their application with numerical tests with SASIR, an implementation of the FISTA, a Forward-Backward splitting algorithm hosted in a LOFAR imager. Various tests have been conducted in Garsden et al., 2015. The main results are: i) an improved angular resolution (super resolution of a factor ≈ 2) with point sources as compared to CLEAN on the same data, ii) correct photometry measurements on a field of point sources at high dynamic range and iii) the imaging of extended sources with improved fidelity. SASIR provides better reconstructions (five time less residuals) of the extended emission as compared to CLEAN. With the advent of large radiotelescopes, there is scope for improving classical imaging methods with convex optimization methods combined with sparse representations.
Causal Network Inference Via Group Sparse Regularization.
Bolstad, Andrew; Van Veen, Barry D; Nowak, Robert
2011-06-11
This paper addresses the problem of inferring sparse causal networks modeled by multivariate autoregressive (MAR) processes. Conditions are derived under which the Group Lasso (gLasso) procedure consistently estimates sparse network structure. The key condition involves a "false connection score" ψ. In particular, we show that consistent recovery is possible even when the number of observations of the network is far less than the number of parameters describing the network, provided that ψ < 1. The false connection score is also demonstrated to be a useful metric of recovery in nonasymptotic regimes. The conditions suggest a modified gLasso procedure which tends to improve the false connection score and reduce the chances of reversing the direction of causal influence. Computational experiments and a real network based electrocorticogram (ECoG) simulation study demonstrate the effectiveness of the approach.
Statistical prediction with Kanerva's sparse distributed memory
NASA Technical Reports Server (NTRS)
Rogers, David
1989-01-01
A new viewpoint of the processing performed by Kanerva's sparse distributed memory (SDM) is presented. In conditions of near- or over-capacity, where the associative-memory behavior of the model breaks down, the processing performed by the model can be interpreted as that of a statistical predictor. Mathematical results are presented which serve as the framework for a new statistical viewpoint of sparse distributed memory and for which the standard formulation of SDM is a special case. This viewpoint suggests possible enhancements to the SDM model, including a procedure for improving the predictiveness of the system based on Holland's work with genetic algorithms, and a method for improving the capacity of SDM even when used as an associative memory.
Solving large sparse eigenvalue problems on supercomputers
NASA Technical Reports Server (NTRS)
Philippe, Bernard; Saad, Youcef
1988-01-01
An important problem in scientific computing consists in finding a few eigenvalues and corresponding eigenvectors of a very large and sparse matrix. The most popular methods to solve these problems are based on projection techniques on appropriate subspaces. The main attraction of these methods is that they only require the use of the matrix in the form of matrix by vector multiplications. The implementations on supercomputers of two such methods for symmetric matrices, namely Lanczos' method and Davidson's method are compared. Since one of the most important operations in these two methods is the multiplication of vectors by the sparse matrix, methods of performing this operation efficiently are discussed. The advantages and the disadvantages of each method are compared and implementation aspects are discussed. Numerical experiments on a one processor CRAY 2 and CRAY X-MP are reported. Possible parallel implementations are also discussed.
Sparse representation for color image restoration.
Mairal, Julien; Elad, Michael; Sapiro, Guillermo
2008-01-01
Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over a redundant dictionary leads to efficient algorithms for handling such sources of data. In particular, the design of well adapted dictionaries for images has been a major challenge. The K-SVD has been recently proposed for this task and shown to perform very well for various grayscale image processing tasks. In this paper, we address the problem of learning dictionaries for color images and extend the K-SVD-based grayscale image denoising algorithm that appears in. This work puts forward ways for handling nonhomogeneous noise and missing information, paving the way to state-of-the-art results in applications such as color image denoising, demosaicing, and inpainting, as demonstrated in this paper. PMID:18229804
Sparse brain network using penalized linear regression
NASA Astrophysics Data System (ADS)
Lee, Hyekyoung; Lee, Dong Soo; Kang, Hyejin; Kim, Boong-Nyun; Chung, Moo K.
2011-03-01
Sparse partial correlation is a useful connectivity measure for brain networks when it is difficult to compute the exact partial correlation in the small-n large-p setting. In this paper, we formulate the problem of estimating partial correlation as a sparse linear regression with a l1-norm penalty. The method is applied to brain network consisting of parcellated regions of interest (ROIs), which are obtained from FDG-PET images of the autism spectrum disorder (ASD) children and the pediatric control (PedCon) subjects. To validate the results, we check their reproducibilities of the obtained brain networks by the leave-one-out cross validation and compare the clustered structures derived from the brain networks of ASD and PedCon.
Causal Network Inference Via Group Sparse Regularization
Bolstad, Andrew; Van Veen, Barry D.; Nowak, Robert
2011-01-01
This paper addresses the problem of inferring sparse causal networks modeled by multivariate autoregressive (MAR) processes. Conditions are derived under which the Group Lasso (gLasso) procedure consistently estimates sparse network structure. The key condition involves a “false connection score” ψ. In particular, we show that consistent recovery is possible even when the number of observations of the network is far less than the number of parameters describing the network, provided that ψ < 1. The false connection score is also demonstrated to be a useful metric of recovery in nonasymptotic regimes. The conditions suggest a modified gLasso procedure which tends to improve the false connection score and reduce the chances of reversing the direction of causal influence. Computational experiments and a real network based electrocorticogram (ECoG) simulation study demonstrate the effectiveness of the approach. PMID:21918591
Neural process reconstruction from sparse user scribbles.
Roberts, Mike; Jeong, Won-Ki; Vázquez-Reina, Amelio; Unger, Markus; Bischof, Horst; Lichtman, Jeff; Pfister, Hanspeter
2011-01-01
We present a novel semi-automatic method for segmenting neural processes in large, highly anisotropic EM (electron microscopy) image stacks. Our method takes advantage of sparse scribble annotations provided by the user to guide a 3D variational segmentation model, thereby allowing our method to globally optimally enforce 3D geometric constraints on the segmentation. Moreover, we leverage a novel algorithm for propagating segmentation constraints through the image stack via optimal volumetric pathways, thereby allowing our method to compute highly accurate 3D segmentations from very sparse user input. We evaluate our method by reconstructing 16 neural processes in a 1024 x 1024 x 50 nanometer-scale EM image stack of a mouse hippocampus. We demonstrate that, on average, our method is 68% more accurate than previous state-of-the-art semi-automatic methods. PMID:22003670
Fingerprint Compression Based on Sparse Representation.
Shao, Guangqi; Wu, Yanping; A, Yong; Liu, Xiao; Guo, Tiande
2014-02-01
A new fingerprint compression algorithm based on sparse representation is introduced. Obtaining an overcomplete dictionary from a set of fingerprint patches allows us to represent them as a sparse linear combination of dictionary atoms. In the algorithm, we first construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l(0)-minimization and then quantize and encode the representation. In this paper, we consider the effect of various factors on compression results. Three groups of fingerprint images are tested. The experiments demonstrate that our algorithm is efficient compared with several competing compression techniques (JPEG, JPEG 2000, and WSQ), especially at high compression ratios. The experiments also illustrate that the proposed algorithm is robust to extract minutiae.
Inpainting with sparse linear combinations of exemplars
Wohlberg, Brendt
2008-01-01
We introduce a new exemplar-based inpainting algorithm based on representing the region to be inpainted as a sparse linear combination of blocks extracted from similar parts of the image being inpainted. This method is conceptually simple, being computed by functional minimization, and avoids the complexity of correctly ordering the filling in of missing regions of other exemplar-based methods. Initial performance comparisons on small inpainting regions indicate that this method provides similar or better performance than other recent methods.
Sparse image reconstruction for molecular imaging.
Ting, Michael; Raich, Raviv; Hero, Alfred O
2009-06-01
The application that motivates this paper is molecular imaging at the atomic level. When discretized at subatomic distances, the volume is inherently sparse. Noiseless measurements from an imaging technology can be modeled by convolution of the image with the system point spread function (psf). Such is the case with magnetic resonance force microscopy (MRFM), an emerging technology where imaging of an individual tobacco mosaic virus was recently demonstrated with nanometer resolution. We also consider additive white Gaussian noise (AWGN) in the measurements. Many prior works of sparse estimators have focused on the case when H has low coherence; however, the system matrix H in our application is the convolution matrix for the system psf. A typical convolution matrix has high coherence. This paper, therefore, does not assume a low coherence H. A discrete-continuous form of the Laplacian and atom at zero (LAZE) p.d.f. used by Johnstone and Silverman is formulated, and two sparse estimators derived by maximizing the joint p.d.f. of the observation and image conditioned on the hyperparameters. A thresholding rule that generalizes the hard and soft thresholding rule appears in the course of the derivation. This so-called hybrid thresholding rule, when used in the iterative thresholding framework, gives rise to the hybrid estimator, a generalization of the lasso. Estimates of the hyperparameters for the lasso and hybrid estimator are obtained via Stein's unbiased risk estimate (SURE). A numerical study with a Gaussian psf and two sparse images shows that the hybrid estimator outperforms the lasso.
Notes on implementation of sparsely distributed memory
NASA Technical Reports Server (NTRS)
Keeler, J. D.; Denning, P. J.
1986-01-01
The Sparsely Distributed Memory (SDM) developed by Kanerva is an unconventional memory design with very interesting and desirable properties. The memory works in a manner that is closely related to modern theories of human memory. The SDM model is discussed in terms of its implementation in hardware. Two appendices discuss the unconventional approaches of the SDM: Appendix A treats a resistive circuit for fast, parallel address decoding; and Appendix B treats a systolic array for high throughput read and write operations.
Splitting: The Development of a Measure.
ERIC Educational Resources Information Center
Gerson, Mary-Joan
1984-01-01
Described the development of a scale that measures splitting as a psychological structure. The construct validity of the splitting scale is suggested by the positive relationship between splitting scores and a diagnostic measure of the narcissistic personality disorder, as well as a negative relationship between splitting scores and levels of…
Modified sparse regularization for electrical impedance tomography.
Fan, Wenru; Wang, Huaxiang; Xue, Qian; Cui, Ziqiang; Sun, Benyuan; Wang, Qi
2016-03-01
Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. It has been widely investigated due to its advantages of low cost, non-radiation, non-invasiveness, and high speed. Image reconstruction of EIT is a nonlinear and ill-posed inverse problem. Therefore, regularization techniques like Tikhonov regularization are used to solve the inverse problem. A sparse regularization based on L1 norm exhibits superiority in preserving boundary information at sharp changes or discontinuous areas in the image. However, the limitation of sparse regularization lies in the time consumption for solving the problem. In order to further improve the calculation speed of sparse regularization, a modified method based on separable approximation algorithm is proposed by using adaptive step-size and preconditioning technique. Both simulation and experimental results show the effectiveness of the proposed method in improving the image quality and real-time performance in the presence of different noise intensities and conductivity contrasts. PMID:27036798
Modified sparse regularization for electrical impedance tomography.
Fan, Wenru; Wang, Huaxiang; Xue, Qian; Cui, Ziqiang; Sun, Benyuan; Wang, Qi
2016-03-01
Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. It has been widely investigated due to its advantages of low cost, non-radiation, non-invasiveness, and high speed. Image reconstruction of EIT is a nonlinear and ill-posed inverse problem. Therefore, regularization techniques like Tikhonov regularization are used to solve the inverse problem. A sparse regularization based on L1 norm exhibits superiority in preserving boundary information at sharp changes or discontinuous areas in the image. However, the limitation of sparse regularization lies in the time consumption for solving the problem. In order to further improve the calculation speed of sparse regularization, a modified method based on separable approximation algorithm is proposed by using adaptive step-size and preconditioning technique. Both simulation and experimental results show the effectiveness of the proposed method in improving the image quality and real-time performance in the presence of different noise intensities and conductivity contrasts.
Aerial Scene Recognition using Efficient Sparse Representation
Cheriyadat, Anil M
2012-01-01
Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.
Mean-field sparse optimal control
Fornasier, Massimo; Piccoli, Benedetto; Rossi, Francesco
2014-01-01
We introduce the rigorous limit process connecting finite dimensional sparse optimal control problems with ODE constraints, modelling parsimonious interventions on the dynamics of a moving population divided into leaders and followers, to an infinite dimensional optimal control problem with a constraint given by a system of ODE for the leaders coupled with a PDE of Vlasov-type, governing the dynamics of the probability distribution of the followers. In the classical mean-field theory, one studies the behaviour of a large number of small individuals freely interacting with each other, by simplifying the effect of all the other individuals on any given individual by a single averaged effect. In this paper, we address instead the situation where the leaders are actually influenced also by an external policy maker, and we propagate its effect for the number N of followers going to infinity. The technical derivation of the sparse mean-field optimal control is realized by the simultaneous development of the mean-field limit of the equations governing the followers dynamics together with the Γ-limit of the finite dimensional sparse optimal control problems. PMID:25288818
SAR Image despeckling via sparse representation
NASA Astrophysics Data System (ADS)
Wang, Zhongmei; Yang, Xiaomei; Zheng, Liang
2014-11-01
SAR image despeckling is an active research area in image processing due to its importance in improving the quality of image for object detection and classification.In this paper, a new approach is proposed for multiplicative noise in SAR image removal based on nonlocal sparse representation by dictionary learning and collaborative filtering. First, a image is divided into many patches, and then a cluster is formed by clustering log-similar image patches using Fuzzy C-means (FCM). For each cluster, an over-complete dictionary is computed using the K-SVD method that iteratively updates the dictionary and the sparse coefficients. The patches belonging to the same cluster are then reconstructed by a sparse combination of the corresponding dictionary atoms. The reconstructed patches are finally collaboratively aggregated to build the denoised image. The experimental results show that the proposed method achieves much better results than many state-of-the-art algorithms in terms of both objective evaluation index (PSNR and ENL) and subjective visual perception.
Efficient visual tracking via low-complexity sparse representation
NASA Astrophysics Data System (ADS)
Lu, Weizhi; Zhang, Jinglin; Kpalma, Kidiyo; Ronsin, Joseph
2015-12-01
Thanks to its good performance on object recognition, sparse representation has recently been widely studied in the area of visual object tracking. Up to now, little attention has been paid to the complexity of sparse representation, while most works are focused on the performance improvement. By reducing the computation load related to sparse representation hundreds of times, this paper proposes by far the most computationally efficient tracking approach based on sparse representation. The proposal simply consists of two stages of sparse representation, one is for object detection and the other for object validation. Experimentally, it achieves better performance than some state-of-the-art methods in both accuracy and speed.
NASA Astrophysics Data System (ADS)
Moniz, Savio J. A.; Blackman, Christopher S.; Southern, Paul; Weaver, Paul M.; Tang, Junwang; Carmalt, Claire J.
2015-10-01
Phase-pure BiFeO3 films were grown directly via dual-source low-pressure CVD (LPCVD) from the ligand-matched precursors [Bi(OtBu)3] and [Fe(OtBu)3]2, without the requirement for oxidising gas or post deposition annealing. Photocatalytic testing for water oxidation revealed extremely high activity for PEC water splitting and photocatalytic water oxidation under visible light irradiation (λ > 420 nm) with a benchmark IPCE for BiFeO3 of 23% at 400 nm. The high activity is ascribed to the ultrafine morphology achieved via the LPCVD process. The performance was enhanced by over four times when the BiFeO3 photoanode is coupled to a Ni-B surface OEC.Phase-pure BiFeO3 films were grown directly via dual-source low-pressure CVD (LPCVD) from the ligand-matched precursors [Bi(OtBu)3] and [Fe(OtBu)3]2, without the requirement for oxidising gas or post deposition annealing. Photocatalytic testing for water oxidation revealed extremely high activity for PEC water splitting and photocatalytic water oxidation under visible light irradiation (λ > 420 nm) with a benchmark IPCE for BiFeO3 of 23% at 400 nm. The high activity is ascribed to the ultrafine morphology achieved via the LPCVD process. The performance was enhanced by over four times when the BiFeO3 photoanode is coupled to a Ni-B surface OEC. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04804d
In vitro suppression of the epidermal Langerhans' cells in necro split skin.
Alsbjörn, B F; Nielsen, S L; Jensen, M G
1987-01-01
The effect of ultraviolet light B irradiation and glucocorticosteroid incubation on the epidermal Langerhans' cell density and tissue viability was investigated, in vitro, on human thin necro split skin.
Semiconductor Nanowires for Photoelectrochemical Water Splitting
NASA Astrophysics Data System (ADS)
Hwang, Yun Jeong
the higher surface potential on the n-TiO 2 (photoanode) side relative to the p-Si (photocathode) side under UV illumination as the result of hole accumulation on the TiO2 side and electron accumulation on the Si side which are desirable charge separation for solar water splitting. In chapter five, TiO2 is replaced with single phase InGaN nanowire in a dual bandgap photoanode to show the potential for solar water splitting with high surface area Si/InGaN hierarchical nanowire arrays and InGaN as a possible candidate for visible light absorber. An enhancement of 5 times in photocurrent was observed when the surface area increased from InGaN nanowires on planar Si to InGaN nanowires on Si wires. Chapter six demonstrates a self-driven water splitting device with the p/n PEC cell which consists of a photocathode and a photoanode. The operating photocurrent (Iop) with the p/n PEC cell is enhanced when n-Si/p-Si photovoltage cell was embedded under an n-TiO2 photoanode by utilizing the photovoltage generated by a Si PV cell. Also, the Si nanowire photocathode surface is modified with Pt and TiO2 to increase hydrogen reducing activity and stability which enhances Iop of the p/n PEC cell as well. When Si/TiO 2 nanowire photocathode is linked with n-Si/p-Si photovoltage cell embedded TiO2 nanowire photoanode, the p/n PEC cell shows water splitting without bias voltage confirmed with 2:1 ratio of hydrogen:oxygen gas evolution and a 92 % Faradic efficiency. These studies represent a significant step towards realizing the benefit of the advanced 1D nanowire configuration for efficient solar to energy conversion.
Split liver transplantation: What's unique?
Dalal, Aparna R
2015-09-24
The intraoperative management of split liver transplantation (SLT) has some unique features as compared to routine whole liver transplantations. Only the liver has this special ability to regenerate that confers benefits in survival and quality of life for two instead of one by splitting livers. Primary graft dysfunction may result from small for size syndrome. Graft weight to recipient body weight ratio is significant for both trisegmental and hemiliver grafts. Intraoperative surgical techniques aim to reduce portal hyperperfusion and decrease venous portal pressure. Ischemic preconditioning can be instituted to protect against ischemic reperfusion injury which impacts graft regeneration. Advancement of the technique of SLT is essential as use of split cadaveric grafts expands the donor pool and potentially has an excellent future. PMID:26421261
Optical coupling and splitting with two parallel waveguide tapers.
Tao, S H
2011-01-17
A coupling and splitting device comprising a width taper and a spatial-modulated subwavelength grating waveguide (SSGW) is proposed. The width taper is a waveguide with increasing width and the SSGW is a waveguide grating whose width and thickness are constant but the filling factor increases along the light propagation. Thus, the effective index of the subwavelength grating increases according to the effective medium theory. Light of orthogonal polarizations from a single-mode fiber can be coupled efficiently with the two parallel tapers. Furthermore, the coupled lights of orthogonal polarizations in the two tapers can be further split with connecting bent waveguides. Fabrication of the device is fully compatible with current complementary metal oxide semiconductor technology.
Split ring containment attachment device
Sammel, Alfred G.
1996-01-01
A containment attachment device 10 for operatively connecting a glovebag 200 to plastic sheeting 100 covering hazardous material. The device 10 includes an inner split ring member 20 connected on one end 22 to a middle ring member 30 wherein the free end 21 of the split ring member 20 is inserted through a slit 101 in the plastic sheeting 100 to captively engage a generally circular portion of the plastic sheeting 100. A collar potion 41 having an outer ring portion 42 is provided with fastening means 51 for securing the device 10 together wherein the glovebag 200 is operatively connected to the collar portion 41.
High efficiency beam splitting for H/sup -/ accelerators
Kramer, S.L.; Stipp, V.; Krieger, C.; Madsen, J.
1985-01-01
Beam splitting for high energy accelerators has typically involved a significant loss of beam and radiation. This paper reports on a new method of splitting beams for H/sup -/ accelerators. This technique uses a high intensity flash of light to strip a fraction of the H/sup -/ beam to H/sup 0/ which are then easily separated by a small bending magnet. A system using a 900-watt (average electrical power) flashlamp and a highly efficient collector will provide 10/sup -3/ to 10/sup -2/ splitting of a 50 MeV H/sup -/ beam. Results on the operation and comparisons with stripping cross sections are presented. Also discussed is the possibility for developing this system to yield a higher stripping fraction.
Causes of anomalous line-splitting in RV Tauri stars
NASA Astrophysics Data System (ADS)
Baird, S. R.
1984-01-01
Data on the anomalous absorption-line splitting and emission in the RV Tauri stars AC Her, U Mon, and R Sct are examined. It is shown that the Karp line-splitting mechanism for cepheids cannot explain the highly redshifted lines that appear without antecedents in some RV Tauri stars and that the veiling that occurs during rising light appears to affect the bluer absorption components more than the high redshift ones. Evidence is reviewed showing strong shock waves must be present in RV Tauri star atmospheres, and a two-shock picture to explain the anomalous line splitting is presented based on a model for long-period variables by Hill and Willson. Advantages and difficulties of the model are discussed.
Manipulating the spin-dependent splitting by geometric Doppler effect.
Liu, Yachao; Ke, Yougang; Zhou, Junxiao; Luo, Hailu; Wen, Shuangchun
2015-06-29
We report the manipulation of spin-dependent splitting by geometric Doppler effect based on dielectric metasurfaces. The extrapolation of rotational Doppler effect from temporal to spatial coordinate gives the phase change when the local optical axes of dielectric metasurfaces are rotating in space. Therefore, the continuous variation of local optical axes in a certain direction will introduce a phase gradient in the same direction at the beam cross section. This is additive to the phase gradient appeared when breaking the rotational symmetry of linearly polarized cylindrical vector beams, which leads to the deflections of different spin components of light, i.e., photonic spin Hall effect. Hence, it is possible to manipulate the spin-dependent splitting by introducing the geometric Doppler effect. Theoretically and experimentally, we show that the magnitude and orientation of the spin-dependent splitting are both tunable when changing the spatial rotation rate of local optical axes and incident polarization.
Mechanistic Understanding of the Plasmonic Enhancement for Solar Water Splitting.
Zhang, Peng; Wang, Tuo; Gong, Jinlong
2015-09-23
H2 generation by solar water splitting is one of the most promising solutions to meet the increasing energy demands of the fast developing society. However, the efficiency of solar-water-splitting systems is still too low for practical applications, which requires further enhancement via different strategies such as doping, construction of heterojunctions, morphology control, and optimization of the crystal structure. Recently, integration of plasmonic metals to semiconductor photocatalysts has been proved to be an effective way to improve their photocatalytic activities. Thus, in-depth understanding of the enhancement mechanisms is of great importance for better utilization of the plasmonic effect. This review describes the relevant mechanisms from three aspects, including: i) light absorption and scattering; ii) hot-electron injection and iii) plasmon-induced resonance energy transfer (PIRET). Perspectives are also proposed to trigger further innovative thinking on plasmonic-enhanced solar water splitting.
Manipulating the spin-dependent splitting by geometric Doppler effect.
Liu, Yachao; Ke, Yougang; Zhou, Junxiao; Luo, Hailu; Wen, Shuangchun
2015-06-29
We report the manipulation of spin-dependent splitting by geometric Doppler effect based on dielectric metasurfaces. The extrapolation of rotational Doppler effect from temporal to spatial coordinate gives the phase change when the local optical axes of dielectric metasurfaces are rotating in space. Therefore, the continuous variation of local optical axes in a certain direction will introduce a phase gradient in the same direction at the beam cross section. This is additive to the phase gradient appeared when breaking the rotational symmetry of linearly polarized cylindrical vector beams, which leads to the deflections of different spin components of light, i.e., photonic spin Hall effect. Hence, it is possible to manipulate the spin-dependent splitting by introducing the geometric Doppler effect. Theoretically and experimentally, we show that the magnitude and orientation of the spin-dependent splitting are both tunable when changing the spatial rotation rate of local optical axes and incident polarization. PMID:26191680
Phasing software for a free flyer space-based sparse mirror array not requiring laser interferometry
NASA Astrophysics Data System (ADS)
Maker, David J.
2004-10-01
This paper presents new software (and simulations) that would phase a space based free flyer sparse array telescope. This particular sparse array method uses mirrors that are far enough away for sensors at the focal point module to detect tip tilt by simply using the deflection of the beam from each mirror. Also the large distance allows these circle six array mirrors to be actuated flats. For piston the secondary actuated mirrors (one for each large mirror segment of these widely spaced sparse array mirrors distributed on a parabola) are moved in real time to maximize the Strehle ratio using the light from the star the planet is revolving around since that star usually has an extremely high SNR (Signal to Noise Ratio). There is then no need for a 6DOF spider web of laser interferometric beams and deep dish mirrors (as in the competing Darwin and JPL methods) to accomplish this. Also the distance between the six 3 meter aperture mirrors could be large (kilometer range) guaranteeing a high resolution and also substantial light gathering power (with these 6 large mirrors) for imaging the details on the surface of extrasolar terrestrial type planets. In any case such a multisatellite free flyer concept would then be no more complex than the European cluster which is now operational. This is a viable concept and a compelling way to image surface detail on extra solar earthlike planets. It is the ideal engineering solution to the problem of space based large baseline sparse arrays. Significant details of the software requirements have been recently developed. In this paper the Fortran code needed to both simulate and operate the actuators in the secondary mirror for this type of sparse array is discussed.
Photosynthetic water splitting: 1987 annual report
Greenbaum, E.
1988-01-01
This document is an annual report of photosynthetic water splitting for the production of hydrogen and oxygen. Unicellular green algae are capable of evolving molecular hydrogen in the presence of carbon dioxide. Controlling factors that determine hydrogen evolution are either temperature or light intensity. Also, mutants of the green alga Chlamydomonas are capable of evolving hydrogen in the presence of carbon dioxide. The significance of these discoveries is that the presence of carbon dioxide (or bicarbonate) is a key factor in determining the activity of the Photosystem II water splitting complex. Second, a new advance in oxygen sensor technology has been made that, for the first time, allows the absolute measurement of photosynthetically evolved oxygen from a single colony of microalgae growing on a solidified agar medium. The key aspect of this electrochemical sensor is the utilization of ultra-pure potassium hydroxide as the electrolyte and a recognition of the role that electrolyte impurities play in contributing to base line noise. 9 refs., 8 figs., 2 tabs.
Dimensionality and geological implications of a sparse magnetotelluric dataset
NASA Astrophysics Data System (ADS)
Derosier, B.; Dennis, K. N.; Plata Martinez, R. O.; Montahaei, M.; Bedrosian, P.; Pellerin, L.
2014-12-01
High-quality broadband magnetotelluric (MT) data (0.01-1000 s period) were acquired at four stations in Borrego Canyon within the Santo Domingo Basin of the Rio Grande Rift, New Mexico, during the 2014 Summer of Applied Geophysical Experience (SAGE) field program. MT response functions along the 10-km long NW trending profile are nearly identical with all stations showing a distinct mode split at 10 s period, suggesting a significant conductivity contrast is located roughly 10-20 km away from the profile based on skin depth estimates. Audiomagnetotelluric, polar diagrams, impedance skew, induction vectors and phase tensor analysis all indicate one-dimensional (1-D) structure at periods <10 sec, a predominantly two-dimensional (2-D) structure at intermediate depths (10-100 s) with a 60° geoelectric strike, and three-dimensional (3-D) structure at the longest periods. Inverse modeling of the data from 0.01-10 s reveals a three-layer electrical structure: a moderately resistive sediments from the surface to ~750 m depth, a conductive layer (weathered volcanoclastics) to 4 km depth, and below 4 km a highly resistive basement of Mesozoic and Precambrian rocks. A 2-D inverse model converged, but resulted in physically unrealistic structure. Hence a 3-D forward model study was performed using the 2014 data together with three additional MT stations acquired further to the east during SAGE 2010. Models that include a NE-trending conductive structure to the north of the profile show broad consistency between the measured and synthetic phase tensors and impedances. We infer our MT data to be on the conductive side of this contact, with the resistive material to the NW attributed to a heavily intruded crust beneath the Jemez lineament, and possibly the edge of the thick lithosphere beneath the Colorado Plateau. 3-D inversion of this sparse data set is being carried out to determine whether this conceptual model is consistent with the full impedance tensor and tipper data.
ERIC Educational Resources Information Center
Carter, Roy A.
1972-01-01
Describes a procedure useful for investigating the effects of substances on plant growth and development. A bean seedling's stem is partially split, and each half is placed in a different nutrient solution. Suggestions for the instructional use of the technique are made. (AL)
NASA Technical Reports Server (NTRS)
Kish, J.
1991-01-01
Geared drive train transmits torque from input shaft in equal parts along two paths in parallel, then combines torques in single output shaft. Scheme reduces load on teeth of meshing gears while furnishing redundancy to protect against failures. Such splitting and recombination of torques common in design of turbine engines.
Galaxy redshift surveys with sparse sampling
Chiang, Chi-Ting; Wullstein, Philipp; Komatsu, Eiichiro; Jee, Inh; Jeong, Donghui; Blanc, Guillermo A.; Ciardullo, Robin; Gronwall, Caryl; Hagen, Alex; Schneider, Donald P.; Drory, Niv; Fabricius, Maximilian; Landriau, Martin; Finkelstein, Steven; Jogee, Shardha; Cooper, Erin Mentuch; Tuttle, Sarah; Gebhardt, Karl; Hill, Gary J.
2013-12-01
Survey observations of the three-dimensional locations of galaxies are a powerful approach to measure the distribution of matter in the universe, which can be used to learn about the nature of dark energy, physics of inflation, neutrino masses, etc. A competitive survey, however, requires a large volume (e.g., V{sub survey} ∼ 10Gpc{sup 3}) to be covered, and thus tends to be expensive. A ''sparse sampling'' method offers a more affordable solution to this problem: within a survey footprint covering a given survey volume, V{sub survey}, we observe only a fraction of the volume. The distribution of observed regions should be chosen such that their separation is smaller than the length scale corresponding to the wavenumber of interest. Then one can recover the power spectrum of galaxies with precision expected for a survey covering a volume of V{sub survey} (rather than the volume of the sum of observed regions) with the number density of galaxies given by the total number of observed galaxies divided by V{sub survey} (rather than the number density of galaxies within an observed region). We find that regularly-spaced sampling yields an unbiased power spectrum with no window function effect, and deviations from regularly-spaced sampling, which are unavoidable in realistic surveys, introduce calculable window function effects and increase the uncertainties of the recovered power spectrum. On the other hand, we show that the two-point correlation function (pair counting) is not affected by sparse sampling. While we discuss the sparse sampling method within the context of the forthcoming Hobby-Eberly Telescope Dark Energy Experiment, the method is general and can be applied to other galaxy surveys.
Guided wavefield reconstruction from sparse measurements
NASA Astrophysics Data System (ADS)
Mesnil, Olivier; Ruzzene, Massimo
2016-02-01
Guided wave measurements are at the basis of several Non-Destructive Evaluation (NDE) techniques. Although sparse measurements of guided wave obtained using piezoelectric sensors can efficiently detect and locate defects, extensive informa-tion on the shape and subsurface location of defects can be extracted from full-field measurements acquired by Laser Doppler Vibrometers (LDV). Wavefield acquisition from LDVs is generally a slow operation due to the fact that the wave propagation to record must be repeated for each point measurement and the initial conditions must be reached between each measurement. In this research, a Sparse Wavefield Reconstruction (SWR) process using Compressed Sensing is developed. The goal of this technique is to reduce the number of point measurements needed to apply NDE techniques by at least one order of magnitude by extrapolating the knowledge of a few randomly chosen measured pixels over an over-sampled grid. To achieve this, the Lamb wave propagation equation is used to formulate a basis of shape functions in which the wavefield has a sparse representation, in order to comply with the Compressed Sensing requirements and use l1-minimization solvers. The main assumption of this reconstruction process is that every material point of the studied area is a potential source. The Compressed Sensing matrix is defined as being the contribution that would have been received at a measurement location from each possible source, using the dispersion relations of the specimen computed using a Semi-Analytical Finite Element technique. The measurements are then processed through an l1-minimizer to find a minimum corresponding to the set of active sources and their corresponding excitation functions. This minimum represents the best combination of the parameters of the model matching the sparse measurements. Wavefields are then reconstructed using the propagation equation. The set of active sources found by minimization contains all the wave
Effective dimension reduction for sparse functional data
YAO, F.; LEI, E.; WU, Y.
2015-01-01
Summary We propose a method of effective dimension reduction for functional data, emphasizing the sparse design where one observes only a few noisy and irregular measurements for some or all of the subjects. The proposed method borrows strength across the entire sample and provides a way to characterize the effective dimension reduction space, via functional cumulative slicing. Our theoretical study reveals a bias-variance trade-off associated with the regularizing truncation and decaying structures of the predictor process and the effective dimension reduction space. A simulation study and an application illustrate the superior finite-sample performance of the method. PMID:26566293
A view of Kanerva's sparse distributed memory
NASA Technical Reports Server (NTRS)
Denning, P. J.
1986-01-01
Pentti Kanerva is working on a new class of computers, which are called pattern computers. Pattern computers may close the gap between capabilities of biological organisms to recognize and act on patterns (visual, auditory, tactile, or olfactory) and capabilities of modern computers. Combinations of numeric, symbolic, and pattern computers may one day be capable of sustaining robots. The overview of the requirements for a pattern computer, a summary of Kanerva's Sparse Distributed Memory (SDM), and examples of tasks this computer can be expected to perform well are given.
Distributed memory compiler design for sparse problems
NASA Technical Reports Server (NTRS)
Wu, Janet; Saltz, Joel; Berryman, Harry; Hiranandani, Seema
1991-01-01
A compiler and runtime support mechanism is described and demonstrated. The methods presented are capable of solving a wide range of sparse and unstructured problems in scientific computing. The compiler takes as input a FORTRAN 77 program enhanced with specifications for distributing data, and the compiler outputs a message passing program that runs on a distributed memory computer. The runtime support for this compiler is a library of primitives designed to efficiently support irregular patterns of distributed array accesses and irregular distributed array partitions. A variety of Intel iPSC/860 performance results obtained through the use of this compiler are presented.
Sparse dynamics for partial differential equations
Schaeffer, Hayden; Caflisch, Russel; Hauck, Cory D.; Osher, Stanley
2013-01-01
We investigate the approximate dynamics of several differential equations when the solutions are restricted to a sparse subset of a given basis. The restriction is enforced at every time step by simply applying soft thresholding to the coefficients of the basis approximation. By reducing or compressing the information needed to represent the solution at every step, only the essential dynamics are represented. In many cases, there are natural bases derived from the differential equations, which promote sparsity. We find that our method successfully reduces the dynamics of convection equations, diffusion equations, weak shocks, and vorticity equations with high-frequency source terms. PMID:23533273
Parallel preconditioning techniques for sparse CG solvers
Basermann, A.; Reichel, B.; Schelthoff, C.
1996-12-31
Conjugate gradient (CG) methods to solve sparse systems of linear equations play an important role in numerical methods for solving discretized partial differential equations. The large size and the condition of many technical or physical applications in this area result in the need for efficient parallelization and preconditioning techniques of the CG method. In particular for very ill-conditioned matrices, sophisticated preconditioner are necessary to obtain both acceptable convergence and accuracy of CG. Here, we investigate variants of polynomial and incomplete Cholesky preconditioners that markedly reduce the iterations of the simply diagonally scaled CG and are shown to be well suited for massively parallel machines.
SKS splitting beneath the eastern United States from Transportable Array data
NASA Astrophysics Data System (ADS)
McNamara, J.; Jackson, K.; Long, M. D.
2014-12-01
Previous studies of SKS splitting beneath the eastern United States have produced evidence for complex and laterally variable anisotropy, including regions that are dominated by null SKS arrivals and those that include multiple layers of anisotropy. One key question is to what extent SKS splitting reflects anisotropy due to present-day flow in the asthenospheric mantle, fossilized anisotropy in the mantle lithosphere due to past deformation processes, or a combination of the two. The broadband station coverage in the eastern US has historically been sparse, but the arrival of the EarthScope USArray Transportable Array (TA) in the eastern US provides an unprecedented opportunity to probe upper mantle anisotropy in detail. Here we present a set of ~3800 SKS splitting measurements at ~380 TA stations east of ~85°W. We identify predominantly null (that is, non-split) SKS arrivals at eastern US stations, with many stations (particularly in the southeastern US) exhibiting clear null arrivals over a wide range of backazimuths. Stations located in the Appalachian Mountains tend to exhibit well-resolved splitting, with typical delay times of ~1 sec and fast directions that are generally parallel to the strike of the mountain range. In the northern part of the study area, we observe more split arrivals, with laterally variable fast directions. Splitting patterns at many individual stations exhibit backazimuthal variations that are consistent with multiple layers of anisotropy, suggesting contributions from both the lithosphere and asthenosphere. Comparisons between fast splitting directions and indicators such as topography, magnetic and gravity anomalies, upper mantle structure derived from tomography, and absolute plate motions reveal that the relative contributions from lithospheric and asthenospheric anisotropy likely vary laterally beneath the eastern US.
Locality constrained joint dynamic sparse representation for local matching based face recognition.
Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun
2014-01-01
Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC. PMID:25419662
Locality Constrained Joint Dynamic Sparse Representation for Local Matching Based Face Recognition
Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun
2014-01-01
Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC. PMID:25419662
Tang Xinde; Ye Hongqi; Liu Hui; Ma Chenxia; Zhao Zhi
2010-01-15
A new visible-light-response photocatalyst Sm{sub 2}InTaO{sub 7} with 4f-d{sup 10}-d{sup 0} configuration crystallized in a cubic system with the space group Fd3m was synthesized by a solid-state reaction method. NiOx-loaded Sm{sub 2}InTaO{sub 7} showed high photocatalytic activities for H{sub 2} evolution from pure water under visible light irradiation (lambda>400 nm). Changes in the photocatalytic activity with the calcination temperature of Sm{sub 2}InTaO{sub 7} and the amount of NiOx loaded indicated that the combination of highly crystallized Sm{sub 2}InTaO{sub 7} and a high dispersion of NiOx particles led to high photocatalytic activity. The high photocatalytic performance of NiOx-loaded Sm{sub 2}InTaO{sub 7} supported the existing view that the photocatalytic activity correlated with the lattice distortion. Density functional theory calculation indicated that strong dispersion from the hybridized In 5s 5p orbitals at the bottom of the conduction band was responsible for the high activity of photocatalyst Sm{sub 2}InTaO{sub 7}. - Graphical abstract: A new visible-light-response photocatalyst Sm{sub 2}InTaO{sub 7} with 4f-d{sup 10}-d{sup 0} configuration was developed. DFT calculation indicated that strong dispersion from the hybridized In 5s 5p orbitals was responsible for the high photocatalytic activity.
Cool covered sky-splitting spectrum-splitting FK
NASA Astrophysics Data System (ADS)
Mohedano, Rubén; Miñano, Juan C.; Benitez, Pablo; Buljan, Marina; Chaves, Julio; Falicoff, Waqidi; Hernandez, Maikel; Sorgato, Simone
2014-09-01
Placing a plane mirror between the primary lens and the receiver in a Fresnel Köhler (FK) concentrator gives birth to a quite different CPV system where all the high-tech components sit on a common plane, that of the primary lens panels. The idea enables not only a thinner device (a half of the original) but also a low cost 1-step manufacturing process for the optics, automatic alignment of primary and secondary lenses, and cell/wiring protection. The concept is also compatible with two different techniques to increase the module efficiency: spectrum splitting between a 3J and a BPC Silicon cell for better usage of Direct Normal Irradiance DNI, and sky splitting to harvest the energy of the diffuse radiation and higher energy production throughout the year. Simple calculations forecast the module would convert 45% of the DNI into electricity.
Cool covered sky-splitting spectrum-splitting FK
Mohedano, Rubén; Chaves, Julio; Falicoff, Waqidi; Hernandez, Maikel; Sorgato, Simone; Miñano, Juan C.; Benitez, Pablo; Buljan, Marina
2014-09-26
Placing a plane mirror between the primary lens and the receiver in a Fresnel Köhler (FK) concentrator gives birth to a quite different CPV system where all the high-tech components sit on a common plane, that of the primary lens panels. The idea enables not only a thinner device (a half of the original) but also a low cost 1-step manufacturing process for the optics, automatic alignment of primary and secondary lenses, and cell/wiring protection. The concept is also compatible with two different techniques to increase the module efficiency: spectrum splitting between a 3J and a BPC Silicon cell for better usage of Direct Normal Irradiance DNI, and sky splitting to harvest the energy of the diffuse radiation and higher energy production throughout the year. Simple calculations forecast the module would convert 45% of the DNI into electricity.
Neonatal Atlas Construction Using Sparse Representation
Shi, Feng; Wang, Li; Wu, Guorong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang
2014-01-01
Atlas construction generally includes first an image registration step to normalize all images into a common space and then an atlas building step to fuse the information from all the aligned images. Although numerous atlas construction studies have been performed to improve the accuracy of the image registration step, unweighted or simply weighted average is often used in the atlas building step. In this article, we propose a novel patch-based sparse representation method for atlas construction after all images have been registered into the common space. By taking advantage of local sparse representation, more anatomical details can be recovered in the built atlas. To make the anatomical structures spatially smooth in the atlas, the anatomical feature constraints on group structure of representations and also the overlapping of neighboring patches are imposed to ensure the anatomical consistency between neighboring patches. The proposed method has been applied to 73 neonatal MR images with poor spatial resolution and low tissue contrast, for constructing a neonatal brain atlas with sharp anatomical details. Experimental results demonstrate that the proposed method can significantly enhance the quality of the constructed atlas by discovering more anatomical details especially in the highly convoluted cortical regions. The resulting atlas demonstrates superior performance of our atlas when applied to spatially normalizing three different neonatal datasets, compared with other start-of-the-art neonatal brain atlases. PMID:24638883
A density functional for sparse matter
NASA Astrophysics Data System (ADS)
Langreth, D. C.; Lundqvist, B. I.; Chakarova-Käck, S. D.; Cooper, V. R.; Dion, M.; Hyldgaard, P.; Kelkkanen, A.; Kleis, J.; Kong, Lingzhu; Li, Shen; Moses, P. G.; Murray, E.; Puzder, A.; Rydberg, H.; Schröder, E.; Thonhauser, T.
2009-02-01
Sparse matter is abundant and has both strong local bonds and weak nonbonding forces, in particular nonlocal van der Waals (vdW) forces between atoms separated by empty space. It encompasses a broad spectrum of systems, like soft matter, adsorption systems and biostructures. Density-functional theory (DFT), long since proven successful for dense matter, seems now to have come to a point, where useful extensions to sparse matter are available. In particular, a functional form, vdW-DF (Dion et al 2004 Phys. Rev. Lett. 92 246401; Thonhauser et al 2007 Phys. Rev. B 76 125112), has been proposed for the nonlocal correlations between electrons and applied to various relevant molecules and materials, including to those layered systems like graphite, boron nitride and molybdenum sulfide, to dimers of benzene, polycyclic aromatic hydrocarbons (PAHs), doped benzene, cytosine and DNA base pairs, to nonbonding forces in molecules, to adsorbed molecules, like benzene, naphthalene, phenol and adenine on graphite, alumina and metals, to polymer and carbon nanotube (CNT) crystals, and hydrogen storage in graphite and metal-organic frameworks (MOFs), and to the structure of DNA and of DNA with intercalators. Comparison with results from wavefunction calculations for the smaller systems and with experimental data for the extended ones show the vdW-DF path to be promising. This could have great ramifications.
Fast Sparse Level Sets on Graphics Hardware.
Jalba, Andrei C; van der Laan, Wladimir J; Roerdink, Jos B T M
2013-01-01
The level-set method is one of the most popular techniques for capturing and tracking deformable interfaces. Although level sets have demonstrated great potential in visualization and computer graphics applications, such as surface editing and physically based modeling, their use for interactive simulations has been limited due to the high computational demands involved. In this paper, we address this computational challenge by leveraging the increased computing power of graphics processors, to achieve fast simulations based on level sets. Our efficient, sparse GPU level-set method is substantially faster than other state-of-the-art, parallel approaches on both CPU and GPU hardware. We further investigate its performance through a method for surface reconstruction, based on GPU level sets. Our novel multiresolution method for surface reconstruction from unorganized point clouds compares favorably with recent, existing techniques and other parallel implementations. Finally, we point out that both level-set computations and rendering of level-set surfaces can be performed at interactive rates, even on large volumetric grids. Therefore, many applications based on level sets can benefit from our sparse level-set method.
Topological sparse learning of dynamic form patterns.
Guthier, T; Willert, V; Eggert, J
2015-01-01
Motion is a crucial source of information for a variety of tasks in social interactions. The process of how humans recognize complex articulated movements such as gestures or face expressions remains largely unclear. There is an ongoing discussion if and how explicit low-level motion information, such as optical flow, is involved in the recognition process. Motivated by this discussion, we introduce a computational model that classifies the spatial configuration of gradient and optical flow patterns. The patterns are learned with an unsupervised learning algorithm based on translation-invariant nonnegative sparse coding called VNMF that extracts prototypical optical flow patterns shaped, for example, as moving heads or limb parts. A key element of the proposed system is a lateral inhibition term that suppresses activations of competing patterns in the learning process, leading to a low number of dominant and topological sparse activations. We analyze the classification performance of the gradient and optical flow patterns on three real-world human action recognition and one face expression recognition data set. The results indicate that the recognition of human actions can be achieved by gradient patterns alone, but adding optical flow patterns increases the classification performance. The combined patterns outperform other biological-inspired models and are competitive with current computer vision approaches. PMID:25248088
Inferring sparse networks for noisy transient processes.
Tran, Hoang M; Bukkapatnam, Satish T S
2016-01-01
Inferring causal structures of real world complex networks from measured time series signals remains an open issue. The current approaches are inadequate to discern between direct versus indirect influences (i.e., the presence or absence of a directed arc connecting two nodes) in the presence of noise, sparse interactions, as well as nonlinear and transient dynamics of real world processes. We report a sparse regression (referred to as the l1-min) approach with theoretical bounds on the constraints on the allowable perturbation to recover the network structure that guarantees sparsity and robustness to noise. We also introduce averaging and perturbation procedures to further enhance prediction scores (i.e., reduce inference errors), and the numerical stability of l1-min approach. Extensive investigations have been conducted with multiple benchmark simulated genetic regulatory network and Michaelis-Menten dynamics, as well as real world data sets from DREAM5 challenge. These investigations suggest that our approach can significantly improve, oftentimes by 5 orders of magnitude over the methods reported previously for inferring the structure of dynamic networks, such as Bayesian network, network deconvolution, silencing and modular response analysis methods based on optimizing for sparsity, transients, noise and high dimensionality issues. PMID:26916813
Inferring sparse networks for noisy transient processes
NASA Astrophysics Data System (ADS)
Tran, Hoang M.; Bukkapatnam, Satish T. S.
2016-02-01
Inferring causal structures of real world complex networks from measured time series signals remains an open issue. The current approaches are inadequate to discern between direct versus indirect influences (i.e., the presence or absence of a directed arc connecting two nodes) in the presence of noise, sparse interactions, as well as nonlinear and transient dynamics of real world processes. We report a sparse regression (referred to as the -min) approach with theoretical bounds on the constraints on the allowable perturbation to recover the network structure that guarantees sparsity and robustness to noise. We also introduce averaging and perturbation procedures to further enhance prediction scores (i.e., reduce inference errors), and the numerical stability of -min approach. Extensive investigations have been conducted with multiple benchmark simulated genetic regulatory network and Michaelis-Menten dynamics, as well as real world data sets from DREAM5 challenge. These investigations suggest that our approach can significantly improve, oftentimes by 5 orders of magnitude over the methods reported previously for inferring the structure of dynamic networks, such as Bayesian network, network deconvolution, silencing and modular response analysis methods based on optimizing for sparsity, transients, noise and high dimensionality issues.
OSKI: A Library of Automatically Tuned Sparse Matrix Kernels
Vuduc, R; Demmel, J W; Yelick, K A
2005-07-19
The Optimized Sparse Kernel Interface (OSKI) is a collection of low-level primitives that provide automatically tuned computational kernels on sparse matrices, for use by solver libraries and applications. These kernels include sparse matrix-vector multiply and sparse triangular solve, among others. The primary aim of this interface is to hide the complex decision-making process needed to tune the performance of a kernel implementation for a particular user's sparse matrix and machine, while also exposing the steps and potentially non-trivial costs of tuning at run-time. This paper provides an overview of OSKI, which is based on our research on automatically tuned sparse kernels for modern cache-based superscalar machines.
NASA Technical Reports Server (NTRS)
Kincaid, D. R.; Young, D. M.
1984-01-01
Adapting and designing mathematical software to achieve optimum performance on the CYBER 205 is discussed. Comments and observations are made in light of recent work done on modifying the ITPACK software package and on writing new software for vector supercomputers. The goal was to develop very efficient vector algorithms and software for solving large sparse linear systems using iterative methods.
Feature Selection and Pedestrian Detection Based on Sparse Representation.
Yao, Shihong; Wang, Tao; Shen, Weiming; Pan, Shaoming; Chong, Yanwen; Ding, Fei
2015-01-01
Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony. PMID:26295480
Feature Selection and Pedestrian Detection Based on Sparse Representation
Yao, Shihong; Wang, Tao; Shen, Weiming; Pan, Shaoming; Chong, Yanwen; Ding, Fei
2015-01-01
Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony. PMID:26295480
Stability of split Stirling refrigerators
NASA Astrophysics Data System (ADS)
de Waele, A. T. A. M.; Liang, W.
2009-02-01
In many thermal systems spontaneous mechanical oscillations are generated under the influence of large temperature gradients. Well-known examples are Taconis oscillations in liquid-helium cryostats and oscillations in thermoacoustic systems. In split Stirling refrigerators the compressor and the cold finger are connected by a flexible tube. The displacer in the cold head is suspended by a spring. Its motion is pneumatically driven by the pressure oscillations generated by the compressor. In this paper we give the basic dynamic equations of split Stirling refrigerators and investigate the possibility of spontaneous mechanical oscillations if a large temperature gradient develops in the cold finger, e.g. during or after cool down. These oscillations would be superimposed on the pressure oscillations of the compressor and could ruin the cooler performance.
Dose-shaping using targeted sparse optimization
Sayre, George A.; Ruan, Dan
2013-07-15
Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, the authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot
Code of Federal Regulations, 2010 CFR
2010-01-01
... 7 Agriculture 2 2010-01-01 2010-01-01 false Split shell. 51.2002 Section 51.2002 Agriculture... Standards for Grades of Filberts in the Shell 1 Definitions § 51.2002 Split shell. Split shell means a shell... of the shell, measured in the direction of the crack....
10 CFR 26.135 - Split specimens.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 10 Energy 1 2010-01-01 2010-01-01 false Split specimens. 26.135 Section 26.135 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.135 Split specimens. (a) If the FFD program follows split-specimen procedures, as described in § 26.113, the licensee...
10 CFR 26.135 - Split specimens.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 1 2013-01-01 2013-01-01 false Split specimens. 26.135 Section 26.135 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.135 Split specimens. (a) If the FFD program follows split-specimen procedures, as described in § 26.113, the licensee...
10 CFR 26.135 - Split specimens.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 1 2012-01-01 2012-01-01 false Split specimens. 26.135 Section 26.135 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.135 Split specimens. (a) If the FFD program follows split-specimen procedures, as described in § 26.113, the licensee...
10 CFR 26.135 - Split specimens.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 1 2014-01-01 2014-01-01 false Split specimens. 26.135 Section 26.135 Energy NUCLEAR REGULATORY COMMISSION FITNESS FOR DUTY PROGRAMS Licensee Testing Facilities § 26.135 Split specimens. (a) If the FFD program follows split-specimen procedures, as described in § 26.113, the licensee...
Split ring containment attachment device
Sammel, A.G.
1995-12-31
A containment attachment device is described for operatively connecting a glovebag to plastic sheeting covering hazardous material. The device includes an inner split ring member connected on one end to a middle ring member wherein the free end of the split ring member is inserted through a slit in the plastic sheeting to captively engage a generally circular portion of the plastic sheeting. A collar portion having an outer ring portion is provided with fastening means for securing the device together wherein the glovebag is operatively connected to the collar portion. Hazardous material such as radioactive waste may be sealed in plastic bags for small items or wrapped in plastic sheeting for large items. Occasionally the need arises to access the hazardous material in a controlled manner, that is, while maintaining total containment. Small items could be placed entirely inside a containment glovebag. However, it may not be possible or practical to place large items inside a containment; instead, one or more glovebags could be attached to the plastic sheeting covering the hazardous material. It is this latter application for which the split ring containment attachment device is intended.
Split torque transmission load sharing
NASA Technical Reports Server (NTRS)
Krantz, T. L.; Rashidi, M.; Kish, J. G.
1992-01-01
Split torque transmissions are attractive alternatives to conventional planetary designs for helicopter transmissions. The split torque designs can offer lighter weight and fewer parts but have not been used extensively for lack of experience, especially with obtaining proper load sharing. Two split torque designs that use different load sharing methods have been studied. Precise indexing and alignment of the geartrain to produce acceptable load sharing has been demonstrated. An elastomeric torque splitter that has large torsional compliance and damping produces even better load sharing while reducing dynamic transmission error and noise. However, the elastomeric torque splitter as now configured is not capable over the full range of operating conditions of a fielded system. A thrust balancing load sharing device was evaluated. Friction forces that oppose the motion of the balance mechanism are significant. A static analysis suggests increasing the helix angle of the input pinion of the thrust balancing design. Also, dynamic analysis of this design predicts good load sharing and significant torsional response to accumulative pitch errors of the gears.
Sparse aperture 3D passive image sensing and recognition
NASA Astrophysics Data System (ADS)
Daneshpanah, Mehdi
The way we perceive, capture, store, communicate and visualize the world has greatly changed in the past century Novel three dimensional (3D) imaging and display systems are being pursued both in academic and industrial settings. In many cases, these systems have revolutionized traditional approaches and/or enabled new technologies in other disciplines including medical imaging and diagnostics, industrial metrology, entertainment, robotics as well as defense and security. In this dissertation, we focus on novel aspects of sparse aperture multi-view imaging systems and their application in quantum-limited object recognition in two separate parts. In the first part, two concepts are proposed. First a solution is presented that involves a generalized framework for 3D imaging using randomly distributed sparse apertures. Second, a method is suggested to extract the profile of objects in the scene through statistical properties of the reconstructed light field. In both cases, experimental results are presented that demonstrate the feasibility of the techniques. In the second part, the application of 3D imaging systems in sensing and recognition of objects is addressed. In particular, we focus on the scenario in which only 10s of photons reach the sensor from the object of interest, as opposed to hundreds of billions of photons in normal imaging conditions. At this level, the quantum limited behavior of light will dominate and traditional object recognition practices may fail. We suggest a likelihood based object recognition framework that incorporates the physics of sensing at quantum-limited conditions. Sensor dark noise has been modeled and taken into account. This framework is applied to 3D sensing of thermal objects using visible spectrum detectors. Thermal objects as cold as 250K are shown to provide enough signature photons to be sensed and recognized within background and dark noise with mature, visible band, image forming optics and detector arrays. The results
Predicting structure in nonsymmetric sparse matrix factorizations
Gilbert, J.R.; Ng, E.G.
1992-10-01
Many computations on sparse matrices have a phase that predicts the nonzero structure of the output, followed by a phase that actually performs the numerical computation. We study structure prediction for computations that involve nonsymmetric row and column permutations and nonsymmetric or non-square matrices. Our tools are bipartite graphs, matchings, and alternating paths. Our main new result concerns LU factorization with partial pivoting. We show that if a square matrix A has the strong Hall property (i.e., is fully indecomposable) then an upper bound due to George and Ng on the nonzero structure of L + U is as tight as possible. To show this, we prove a crucial result about alternating paths in strong Hall graphs. The alternating-paths theorem seems to be of independent interest: it can also be used to prove related results about structure prediction for QR factorization that are due to Coleman, Edenbrandt, Gilbert, Hare, Johnson, Olesky, Pothen, and van den Driessche.
ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES
Fan, Jianqing; Rigollet, Philippe; Wang, Weichen
2016-01-01
High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓr norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics. PMID:26806986
Sparse distributed memory and related models
NASA Technical Reports Server (NTRS)
Kanerva, Pentti
1992-01-01
Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.
Eigensolver for a Sparse, Large Hermitian Matrix
NASA Technical Reports Server (NTRS)
Tisdale, E. Robert; Oyafuso, Fabiano; Klimeck, Gerhard; Brown, R. Chris
2003-01-01
A parallel-processing computer program finds a few eigenvalues in a sparse Hermitian matrix that contains as many as 100 million diagonal elements. This program finds the eigenvalues faster, using less memory, than do other, comparable eigensolver programs. This program implements a Lanczos algorithm in the American National Standards Institute/ International Organization for Standardization (ANSI/ISO) C computing language, using the Message Passing Interface (MPI) standard to complement an eigensolver in PARPACK. [PARPACK (Parallel Arnoldi Package) is an extension, to parallel-processing computer architectures, of ARPACK (Arnoldi Package), which is a collection of Fortran 77 subroutines that solve large-scale eigenvalue problems.] The eigensolver runs on Beowulf clusters of computers at the Jet Propulsion Laboratory (JPL).
Compressed Sensing for Reconstructing Sparse Quantum States
NASA Astrophysics Data System (ADS)
Rudinger, Kenneth; Joynt, Robert
2014-03-01
Compressed sensing techniques have been successfully applied to quantum state tomography, enabling the efficient determination of states that are nearly pure, i.e, of low rank. We show how compressed sensing may be used even when the states to be reconstructed are full rank. Instead, the necessary requirement is that the states be sparse in some known basis (e.g. the Pauli basis). Physical systems at high temperatures in thermal equilibrium are important examples of such states. Using this method, we are able to demonstrate that, like for classical signals, compressed sensing for quantum states exhibits the Donoho-Tanner phase transition. This method will be useful for the determination of the Hamiltonians of artificially constructed quantum systems whose purpose is to simulate condensed-matter models, as it requires many fewer measurements than demanded by standard tomographic procedures. This work was supported in part by ARO, DOD (W911NF-09-1-0439) and NSF (CCR-0635355).
Blind source separation by sparse decomposition
NASA Astrophysics Data System (ADS)
Zibulevsky, Michael; Pearlmutter, Barak A.
2000-04-01
The blind source separation problem is to extract the underlying source signals from a set of their linear mixtures, where the mixing matrix is unknown. This situation is common, eg in acoustics, radio, and medical signal processing. We exploit the property of the sources to have a sparse representation in a corresponding signal dictionary. Such a dictionary may consist of wavelets, wavelet packets, etc., or be obtained by learning from a given family of signals. Starting from the maximum a posteriori framework, which is applicable to the case of more sources than mixtures, we derive a few other categories of objective functions, which provide faster and more robust computations, when there are an equal number of sources and mixtures. Our experiments with artificial signals and with musical sounds demonstrate significantly better separation than other known techniques.
Fast generation of sparse random kernel graphs
Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo
2015-09-10
The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in time at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.
Fast generation of sparse random kernel graphs
Hagberg, Aric; Lemons, Nathan; Du, Wen -Bo
2015-09-10
The development of kernel-based inhomogeneous random graphs has provided models that are flexible enough to capture many observed characteristics of real networks, and that are also mathematically tractable. We specify a class of inhomogeneous random graph models, called random kernel graphs, that produces sparse graphs with tunable graph properties, and we develop an efficient generation algorithm to sample random instances from this model. As real-world networks are usually large, it is essential that the run-time of generation algorithms scales better than quadratically in the number of vertices n. We show that for many practical kernels our algorithm runs in timemore » at most ο(n(logn)²). As an example, we show how to generate samples of power-law degree distribution graphs with tunable assortativity.« less
Integer sparse distributed memory: analysis and results.
Snaider, Javier; Franklin, Stan; Strain, Steve; George, E Olusegun
2013-10-01
Sparse distributed memory is an auto-associative memory system that stores high dimensional Boolean vectors. Here we present an extension of the original SDM, the Integer SDM that uses modular arithmetic integer vectors rather than binary vectors. This extension preserves many of the desirable properties of the original SDM: auto-associativity, content addressability, distributed storage, and robustness over noisy inputs. In addition, it improves the representation capabilities of the memory and is more robust over normalization. It can also be extended to support forgetting and reliable sequence storage. We performed several simulations that test the noise robustness property and capacity of the memory. Theoretical analyses of the memory's fidelity and capacity are also presented. PMID:23747569
Convolutional Sparse Coding for Trajectory Reconstruction.
Zhu, Yingying; Lucey, Simon
2015-03-01
Trajectory basis Non-Rigid Structure from Motion (NRSfM) refers to the process of reconstructing the 3D trajectory of each point of a non-rigid object from just their 2D projected trajectories. Reconstruction relies on two factors: (i) the condition of the composed camera & trajectory basis matrix, and (ii) whether the trajectory basis has enough degrees of freedom to model the 3D point trajectory. These two factors are inherently conflicting. Employing a trajectory basis with small capacity has the positive characteristic of reducing the likelihood of an ill-conditioned system (when composed with the camera) during reconstruction. However, this has the negative characteristic of increasing the likelihood that the basis will not be able to fully model the object's "true" 3D point trajectories. In this paper we draw upon a well known result centering around the Reduced Isometry Property (RIP) condition for sparse signal reconstruction. RIP allow us to relax the requirement that the full trajectory basis composed with the camera matrix must be well conditioned. Further, we propose a strategy for learning an over-complete basis using convolutional sparse coding from naturally occurring point trajectory corpora to increase the likelihood that the RIP condition holds for a broad class of point trajectories and camera motions. Finally, we propose an l1 inspired objective for trajectory reconstruction that is able to "adaptively" select the smallest sub-matrix from an over-complete trajectory basis that balances (i) and (ii). We present more practical 3D reconstruction results compared to current state of the art in trajectory basis NRSfM.
Miniature Laboratory for Detecting Sparse Biomolecules
NASA Technical Reports Server (NTRS)
Lin, Ying; Yu, Nan
2005-01-01
A miniature laboratory system has been proposed for use in the field to detect sparsely distributed biomolecules. By emphasizing concentration and sorting of specimens prior to detection, the underlying system concept would make it possible to attain high detection sensitivities without the need to develop ever more sensitive biosensors. The original purpose of the proposal is to aid the search for signs of life on a remote planet by enabling the detection of specimens as sparse as a few molecules or microbes in a large amount of soil, dust, rocks, water/ice, or other raw sample material. Some version of the system could prove useful on Earth for remote sensing of biological contamination, including agents of biological warfare. Processing in this system would begin with dissolution of the raw sample material in a sample-separation vessel. The solution in the vessel would contain floating microscopic magnetic beads coated with substances that could engage in chemical reactions with various target functional groups that are parts of target molecules. The chemical reactions would cause the targeted molecules to be captured on the surfaces of the beads. By use of a controlled magnetic field, the beads would be concentrated in a specified location in the vessel. Once the beads were thus concentrated, the rest of the solution would be discarded. This procedure would obviate the filtration steps and thereby also eliminate the filter-clogging difficulties of typical prior sample-concentration schemes. For ferrous dust/soil samples, the dissolution would be done first in a separate vessel before the solution is transferred to the microbead-containing vessel.
Alternating tip splitting in directional solidification.
Utter, B; Ragnarsson, R; Bodenschatz, E
2001-05-14
We report experimental results on the tip splitting dynamics of seaweed growth in directional solidification of succinonitrile alloys. Despite the random appearance of the growth, a tip splitting morphology was observed in which the tip alternately splits to the left and to the right. The tip splitting frequency f was found to be related to the growth velocity V as a power law f~V1.5. This finding is consistent with the predictions of a tip splitting model that is also presented. Small anisotropies are shown to lead to different kinds of seaweed morphologies.
Zhang, Di; He, Jiazhong; Zhao, Yun; Du, Minghui
2015-03-01
In magnetic resonance (MR) imaging, image spatial resolution is determined by various instrumental limitations and physical considerations. This paper presents a new algorithm for producing a high-resolution version of a low-resolution MR image. The proposed method consists of two consecutive steps: (1) reconstructs a high-resolution MR image from a given low-resolution observation via solving a joint sparse representation and nonlocal similarity L1-norm minimization problem; and (2) applies a sparse derivative prior based post-processing to suppress blurring effects. Extensive experiments on simulated brain MR images and two real clinical MR image datasets validate that the proposed method achieves much better results than many state-of-the-art algorithms in terms of both quantitative measures and visual perception.
An Optically Transparent Iron Nickel Oxide Catalyst for Solar Water Splitting.
Morales-Guio, Carlos G; Mayer, Matthew T; Yella, Aswani; Tilley, S David; Grätzel, Michael; Hu, Xile
2015-08-12
Sunlight-driven water splitting to produce hydrogen fuel is an attractive method for renewable energy conversion. Tandem photoelectrochemical water splitting devices utilize two photoabsorbers to harvest the sunlight and drive the water splitting reaction. The absorption of sunlight by electrocatalysts is a severe problem for tandem water splitting devices where light needs to be transmitted through the larger bandgap component to illuminate the smaller bandgap component. Herein, we describe a novel method for the deposition of an optically transparent amorphous iron nickel oxide oxygen evolution electrocatalyst. The catalyst was deposited on both thin film and high-aspect ratio nanostructured hematite photoanodes. The low catalyst loading combined with its high activity at low overpotential results in significant improvement on the onset potential for photoelectrochemical water oxidation. This transparent catalyst further enables the preparation of a stable hematite/perovskite solar cell tandem device, which performs unassisted water splitting.
Weighted sparse representation for human ear recognition based on local descriptor
NASA Astrophysics Data System (ADS)
Mawloud, Guermoui; Djamel, Melaab
2016-01-01
A two-stage ear recognition framework is presented where two local descriptors and a sparse representation algorithm are combined. In a first stage, the algorithm proceeds by deducing a subset of the closest training neighbors to the test ear sample. The selection is based on the K-nearest neighbors classifier in the pattern of oriented edge magnitude feature space. In a second phase, the co-occurrence of adjacent local binary pattern features are extracted from the preselected subset and combined to form a dictionary. Afterward, sparse representation classifier is employed on the developed dictionary in order to infer the closest element to the test sample. Thus, by splitting up the ear image into a number of segments and applying the described recognition routine on each of them, the algorithm finalizes by attributing a final class label based on majority voting over the individual labels pointed out by each segment. Experimental results demonstrate the effectiveness as well as the robustness of the proposed scheme over leading state-of-the-art methods. Especially when the ear image is occluded, the proposed algorithm exhibits a great robustness and reaches the recognition performances outlined in the state of the art.
Cervigram image segmentation based on reconstructive sparse representations
NASA Astrophysics Data System (ADS)
Zhang, Shaoting; Huang, Junzhou; Wang, Wei; Huang, Xiaolei; Metaxas, Dimitris
2010-03-01
We proposed an approach based on reconstructive sparse representations to segment tissues in optical images of the uterine cervix. Because of large variations in image appearance caused by the changing of the illumination and specular reflection, the color and texture features in optical images often overlap with each other and are not linearly separable. By leveraging sparse representations the data can be transformed to higher dimensions with sparse constraints and become more separated. K-SVD algorithm is employed to find sparse representations and corresponding dictionaries. The data can be reconstructed from its sparse representations and positive and/or negative dictionaries. Classification can be achieved based on comparing the reconstructive errors. In the experiments we applied our method to automatically segment the biomarker AcetoWhite (AW) regions in an archive of 60,000 images of the uterine cervix. Compared with other general methods, our approach showed lower space and time complexity and higher sensitivity.
Sparse Coding on Symmetric Positive Definite Manifolds Using Bregman Divergences.
Harandi, Mehrtash T; Hartley, Richard; Lovell, Brian; Sanderson, Conrad
2016-06-01
This paper introduces sparse coding and dictionary learning for symmetric positive definite (SPD) matrices, which are often used in machine learning, computer vision, and related areas. Unlike traditional sparse coding schemes that work in vector spaces, in this paper, we discuss how SPD matrices can be described by sparse combination of dictionary atoms, where the atoms are also SPD matrices. We propose to seek sparse coding by embedding the space of SPD matrices into the Hilbert spaces through two types of the Bregman matrix divergences. This not only leads to an efficient way of performing sparse coding but also an online and iterative scheme for dictionary learning. We apply the proposed methods to several computer vision tasks where images are represented by region covariance matrices. Our proposed algorithms outperform state-of-the-art methods on a wide range of classification tasks, including face recognition, action recognition, material classification, and texture categorization. PMID:25643414
Photoelectrochemical water splitting at titanium dioxide nanotubes coated with tungsten trioxide
Park, Jong Hyeok; Park, O Ok; Kim, Sungwook
2006-10-16
The photocatalytic splitting of water into hydrogen and oxygen using solar light is a potentially clean and renewable source for hydrogen fuel. Titanium oxide nanotubes coated with tungsten oxide were prepared to harvest more solar light for the first time and characterized their water splitting efficiency. The tungsten trioxide coatings significantly enhanced the visible spectrum absorption of the titanium dioxide nanotube array, as well as their solar-spectrum induced photocurrents. For the sample, upon white light illumination at 150 mW/cm{sup 2}, hydrogen gas generated at the overall conversion efficiency of 0.87%.
Laser-induced nuclear magnetic resonance splitting in hydrocarbons.
Ikäläinen, Suvi; Lantto, Perttu; Manninen, Pekka; Vaara, Juha
2008-09-28
Irradiation of matter with circularly polarized light (CPL) shifts all nuclear magnetic resonance (NMR) lines. The phenomenon arises from the second-order interaction of the electron cloud with the optical field, combined with the orbital hyperfine interaction. The shift occurs in opposite directions for right and left CPL, and rapid switching between them will split the resonance lines into two. We present ab initio and density functional theory predictions of laser-induced NMR splittings for hydrocarbon systems with different sizes: ethene, benzene, coronene, fullerene, and circumcoronene. Due to the computationally challenging nature of the effect, traditional basis sets could not be used for the larger systems. A novel method for generating basis sets, mathematical completeness optimization, was employed. As expected, the magnitude of the spectral splitting increases with the laser beam frequency and polarizability of the system. Massive amplification of the effect is also observed close to the optical excitation energies. A much larger laser-induced splitting is found for the largest of the present molecules than for the previously investigated noble gas atoms or small molecules. The laser intensity required for experimental detection of the effect is discussed.
Split Dirac supersymmetry: An ultraviolet completion of Higgsino dark matter
NASA Astrophysics Data System (ADS)
Fox, Patrick J.; Kribs, Graham D.; Martin, Adam
2014-10-01
Motivated by the observation that the Higgs quartic coupling runs to zero at an intermediate scale, we propose a new framework for models of split supersymmetry, in which gauginos acquire intermediate scale Dirac masses of ˜108-11 GeV. Scalar masses arise from one-loop finite contributions as well as direct gravity-mediated contributions. Like split supersymmetry, one Higgs doublet is fine-tuned to be light. The scale at which the Dirac gauginos are introduced to make the Higgs quartic zero is the same as is necessary for gauge coupling unification. Thus, gauge coupling unification persists (nontrivially, due to adjoint multiplets), though with a somewhat higher unification scale ≳1017 GeV. The μ term is naturally at the weak scale, and provides an opportunity for experimental verification. We present two manifestations of split Dirac supersymmetry. In the "pure Dirac" model, the lightest Higgsino must decay through R-parity violating couplings, leading to an array of interesting signals in colliders. In the "hypercharge impure" model, the bino acquires a Majorana mass that is one-loop suppressed compared with the Dirac gluino and wino. This leads to weak scale Higgsino dark matter whose overall mass scale, as well as the mass splitting between the neutral components, is naturally generated from the same UV dynamics. We outline the challenges to discovering pseudo-Dirac Higgsino dark matter in collider and dark matter detection experiments.
Split quaternion nonlinear adaptive filtering.
Ujang, Bukhari Che; Took, Clive Cheong; Mandic, Danilo P
2010-04-01
A split quaternion learning algorithm for the training of nonlinear finite impulse response adaptive filters for the processing of three- and four-dimensional signals is proposed. The derivation takes into account the non-commutativity of the quaternion product, an aspect neglected in the derivation of the existing learning algorithms. It is shown that the additional information taken into account by a rigorous treatment of quaternion algebra provides improved performance on hypercomplex processes. A rigorous analysis of the convergence of the proposed algorithms is also provided. Simulations on both benchmark and real-world signals support the approach.
ERIC Educational Resources Information Center
Sadler, Peter G.
The Institute for the Study of Sparsely Populated Areas is a multidisciplinary research unit which acts to coordinate, further, and initiate studies of the economic and social conditions of sparsely populated areas. Short summaries of the eight studies completed in the session of 1977-78 indicate work in such areas as the study of political life…
A Variable Splitting based Algorithm for Fast Multi-Coil Blind Compressed Sensing MRI reconstruction
Bhave, Sampada; Lingala, Sajan Goud; Jacob, Mathews
2015-01-01
Recent work on blind compressed sensing (BCS) has shown that exploiting sparsity in dictionaries that are learnt directly from the data at hand can outperform compressed sensing (CS) that uses fixed dictionaries. A challenge with BCS however is the large computational complexity during its optimization, which limits its practical use in several MRI applications. In this paper, we propose a novel optimization algorithm that utilize variable splitting strategies to significantly improve the convergence speed of the BCS optimization. The splitting allows us to efficiently decouple the sparse coefficient, and dictionary update steps from the data fidelity term, resulting in subproblems that take closed form analytical solutions, which otherwise require slower iterative conjugate gradient algorithms. Through experiments on multi coil parametric MRI data, we demonstrate the superior performance of BCS, while achieving convergence speed up factors of over 15 fold over the previously proposed implementation of the BCS algorithm. PMID:25570473
A Statistical Survey of Sprite Streamer Splitting
NASA Astrophysics Data System (ADS)
Haaland, R. K.; McHarg, M. G.; Stenbaek-Nielsen, H. C.; Liu, N.; Kanmae, T.
2014-12-01
A fundamental understanding of streamers includes the dynamics of streamer tip splitting. Previous work has shown that sprite streamers become wider and brighter immediately before splitting (McHarg et. al [2010].) We extend this work and present a statistical survey of sprite streamer splitting and propagation based on observations made with two intensified, high-speed, CMOS cameras with high temporal and spatial resolution. We determine the number of streamer tips present after splitting and the number of splitting events as a function of angle from the local vertical for a variety of different sprites. We also compare the relative distances between splits, as well as the streamer widths immediately preceding splitting for different sprite events. Where feasible we triangulate the altitudes of the splitting events and categorize them based on the distance, and time, from the causative lightning strike. We relate these measurements to the physical processes that may lead to streamer tip splitting. McHarg, M. G., H. C. Stenbaek-Nielsen, T. Kanmae, and R. K. Haaland (2010), Streamer tip splitting in sprites, J. Geophys. Res., 115, A00E53, doi:10.1029/2009JA014850.
Marangoni, M; Janner, D; Ramponi, R; Laporta, P; Longhi, S; Cianci, E; Foglietti, V
2005-08-01
A theoretical and experimental analysis of beam dynamics and wave packet splitting of light in a periodically bent optical waveguide, a phenomenon recently observed [Phys. Rev. Lett. 94, 073002 (2005)] which is the optical equivalent of adiabatic stabilization of atoms in intense and high-frequency laser fields, is presented in the multimode operational regime. Inhibition of wave packet splitting is theoretically predicted and experimentally observed for higher-order mode excitation.
Generation of dense statistical connectomes from sparse morphological data
Egger, Robert; Dercksen, Vincent J.; Udvary, Daniel; Hege, Hans-Christian; Oberlaender, Marcel
2014-01-01
Sensory-evoked signal flow, at cellular and network levels, is primarily determined by the synaptic wiring of the underlying neuronal circuitry. Measurements of synaptic innervation, connection probabilities and subcellular organization of synaptic inputs are thus among the most active fields of research in contemporary neuroscience. Methods to measure these quantities range from electrophysiological recordings over reconstructions of dendrite-axon overlap at light-microscopic levels to dense circuit reconstructions of small volumes at electron-microscopic resolution. However, quantitative and complete measurements at subcellular resolution and mesoscopic scales to obtain all local and long-range synaptic in/outputs for any neuron within an entire brain region are beyond present methodological limits. Here, we present a novel concept, implemented within an interactive software environment called NeuroNet, which allows (i) integration of sparsely sampled (sub)cellular morphological data into an accurate anatomical reference frame of the brain region(s) of interest, (ii) up-scaling to generate an average dense model of the neuronal circuitry within the respective brain region(s) and (iii) statistical measurements of synaptic innervation between all neurons within the model. We illustrate our approach by generating a dense average model of the entire rat vibrissal cortex, providing the required anatomical data, and illustrate how to measure synaptic innervation statistically. Comparing our results with data from paired recordings in vitro and in vivo, as well as with reconstructions of synaptic contact sites at light- and electron-microscopic levels, we find that our in silico measurements are in line with previous results. PMID:25426033
Biogenesis of water splitting by photosystem II during de-etiolation of barley (Hordeum vulgare L.).
Shevela, Dmitriy; Arnold, Janine; Reisinger, Veronika; Berends, Hans-Martin; Kmiec, Karol; Koroidov, Sergey; Bue, Ann Kristin; Messinger, Johannes; Eichacker, Lutz A
2016-07-01
Etioplasts lack thylakoid membranes and photosystem complexes. Light triggers differentiation of etioplasts into mature chloroplasts, and photosystem complexes assemble in parallel with thylakoid membrane development. Plastids isolated at various time points of de-etiolation are ideal to study the kinetic biogenesis of photosystem complexes during chloroplast development. Here, we investigated the chronology of photosystem II (PSII) biogenesis by monitoring assembly status of chlorophyll-binding protein complexes and development of water splitting via O2 production in plastids (etiochloroplasts) isolated during de-etiolation of barley (Hordeum vulgare L.). Assembly of PSII monomers, dimers and complexes binding outer light-harvesting antenna [PSII-light-harvesting complex II (LHCII) supercomplexes] was identified after 1, 2 and 4 h of de-etiolation, respectively. Water splitting was detected in parallel with assembly of PSII monomers, and its development correlated with an increase of bound Mn in the samples. After 4 h of de-etiolation, etiochloroplasts revealed the same water-splitting efficiency as mature chloroplasts. We conclude that the capability of PSII to split water during de-etiolation precedes assembly of the PSII-LHCII supercomplexes. Taken together, data show a rapid establishment of water-splitting activity during etioplast-to-chloroplast transition and emphasize that assembly of the functional water-splitting site of PSII is not the rate-limiting step in the formation of photoactive thylakoid membranes.
NASA Astrophysics Data System (ADS)
Jiang, Tongsong; Jiang, Ziwu; Zhang, Zhaozhong
2015-08-01
In the study of the relation between complexified classical and non-Hermitian quantum mechanics, physicists found that there are links to quaternionic and split quaternionic mechanics, and this leads to the possibility of employing algebraic techniques of split quaternions to tackle some problems in complexified classical and quantum mechanics. This paper, by means of real representation of a split quaternion matrix, studies the problem of diagonalization of a split quaternion matrix and gives algebraic techniques for diagonalization of split quaternion matrices in split quaternionic mechanics.
Jiang, Tongsong; Jiang, Ziwu; Zhang, Zhaozhong
2015-08-15
In the study of the relation between complexified classical and non-Hermitian quantum mechanics, physicists found that there are links to quaternionic and split quaternionic mechanics, and this leads to the possibility of employing algebraic techniques of split quaternions to tackle some problems in complexified classical and quantum mechanics. This paper, by means of real representation of a split quaternion matrix, studies the problem of diagonalization of a split quaternion matrix and gives algebraic techniques for diagonalization of split quaternion matrices in split quaternionic mechanics.
Sparse distributed memory: Principles and operation
NASA Technical Reports Server (NTRS)
Flynn, M. J.; Kanerva, P.; Bhadkamkar, N.
1989-01-01
Sparse distributed memory is a generalized random access memory (RAM) for long (1000 bit) binary words. Such words can be written into and read from the memory, and they can also be used to address the memory. The main attribute of the memory is sensitivity to similarity, meaning that a word can be read back not only by giving the original write address but also by giving one close to it as measured by the Hamming distance between addresses. Large memories of this kind are expected to have wide use in speech recognition and scene analysis, in signal detection and verification, and in adaptive control of automated equipment, in general, in dealing with real world information in real time. The memory can be realized as a simple, massively parallel computer. Digital technology has reached a point where building large memories is becoming practical. Major design issues were resolved which were faced in building the memories. The design is described of a prototype memory with 256 bit addresses and from 8 to 128 K locations for 256 bit words. A key aspect of the design is extensive use of dynamic RAM and other standard components.
Approximation and compression with sparse orthonormal transforms.
Sezer, Osman Gokhan; Guleryuz, Onur G; Altunbasak, Yucel
2015-08-01
We propose a new transform design method that targets the generation of compression-optimized transforms for next-generation multimedia applications. The fundamental idea behind transform compression is to exploit regularity within signals such that redundancy is minimized subject to a fidelity cost. Multimedia signals, in particular images and video, are well known to contain a diverse set of localized structures, leading to many different types of regularity and to nonstationary signal statistics. The proposed method designs sparse orthonormal transforms (SOTs) that automatically exploit regularity over different signal structures and provides an adaptation method that determines the best representation over localized regions. Unlike earlier work that is motivated by linear approximation constructs and model-based designs that are limited to specific types of signal regularity, our work uses general nonlinear approximation ideas and a data-driven setup to significantly broaden its reach. We show that our SOT designs provide a safe and principled extension of the Karhunen-Loeve transform (KLT) by reducing to the KLT on Gaussian processes and by automatically exploiting non-Gaussian statistics to significantly improve over the KLT on more general processes. We provide an algebraic optimization framework that generates optimized designs for any desired transform structure (multiresolution, block, lapped, and so on) with significantly better n -term approximation performance. For each structure, we propose a new prototype codec and test over a database of images. Simulation results show consistent increase in compression and approximation performance compared with conventional methods. PMID:25823033
Sparse alignment for robust tensor learning.
Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Zhao, Cairong; Sun, Mingming
2014-10-01
Multilinear/tensor extensions of manifold learning based algorithms have been widely used in computer vision and pattern recognition. This paper first provides a systematic analysis of the multilinear extensions for the most popular methods by using alignment techniques, thereby obtaining a general tensor alignment framework. From this framework, it is easy to show that the manifold learning based tensor learning methods are intrinsically different from the alignment techniques. Based on the alignment framework, a robust tensor learning method called sparse tensor alignment (STA) is then proposed for unsupervised tensor feature extraction. Different from the existing tensor learning methods, L1- and L2-norms are introduced to enhance the robustness in the alignment step of the STA. The advantage of the proposed technique is that the difficulty in selecting the size of the local neighborhood can be avoided in the manifold learning based tensor feature extraction algorithms. Although STA is an unsupervised learning method, the sparsity encodes the discriminative information in the alignment step and provides the robustness of STA. Extensive experiments on the well-known image databases as well as action and hand gesture databases by encoding object images as tensors demonstrate that the proposed STA algorithm gives the most competitive performance when compared with the tensor-based unsupervised learning methods. PMID:25291733
Optimal parallel solution of sparse triangular systems
NASA Technical Reports Server (NTRS)
Alvarado, Fernando L.; Schreiber, Robert
1990-01-01
A method for the parallel solution of triangular sets of equations is described that is appropriate when there are many right-handed sides. By preprocessing, the method can reduce the number of parallel steps required to solve Lx = b compared to parallel forward or backsolve. Applications are to iterative solvers with triangular preconditioners, to structural analysis, or to power systems applications, where there may be many right-handed sides (not all available a priori). The inverse of L is represented as a product of sparse triangular factors. The problem is to find a factored representation of this inverse of L with the smallest number of factors (or partitions), subject to the requirement that no new nonzero elements be created in the formation of these inverse factors. A method from an earlier reference is shown to solve this problem. This method is improved upon by constructing a permutation of the rows and columns of L that preserves triangularity and allow for the best possible such partition. A number of practical examples and algorithmic details are presented. The parallelism attainable is illustrated by means of elimination trees and clique trees.
Visual Exploration of Sparse Traffic Trajectory Data.
Wang, Zuchao; Ye, Tangzhi; Lu, Min; Yuan, Xiaoru; Qu, Huamin; Yuan, Jacky; Wu, Qianliang
2014-12-01
In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro-traffic analysis. However, the vehicle movements are recorded only when they pass through the cells. The exact tracks between two consecutive cells are unknown. To deal with such uncertainties, we first design a local animation, showing the vehicle movements only in the vicinity of cells. Besides, we ignore the micro-behaviors of individual vehicles, and focus on the macro-traffic patterns. We apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. Beyond that, we propose to study the correlation between these two patterns with dynamic graph visualization techniques. It allows us to check how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. Case studies show the effectiveness of our system. PMID:26356895
Sparse coding for layered neural networks
NASA Astrophysics Data System (ADS)
Katayama, Katsuki; Sakata, Yasuo; Horiguchi, Tsuyoshi
2002-07-01
We investigate storage capacity of two types of fully connected layered neural networks with sparse coding when binary patterns are embedded into the networks by a Hebbian learning rule. One of them is a layered network, in which a transfer function of even layers is different from that of odd layers. The other is a layered network with intra-layer connections, in which the transfer function of inter-layer is different from that of intra-layer, and inter-layered neurons and intra-layered neurons are updated alternately. We derive recursion relations for order parameters by means of the signal-to-noise ratio method, and then apply the self-control threshold method proposed by Dominguez and Bollé to both layered networks with monotonic transfer functions. We find that a critical value αC of storage capacity is about 0.11|a ln a| -1 ( a≪1) for both layered networks, where a is a neuronal activity. It turns out that the basin of attraction is larger for both layered networks when the self-control threshold method is applied.
Partitioning sparse matrices with eigenvectors of graphs
NASA Technical Reports Server (NTRS)
Pothen, Alex; Simon, Horst D.; Liou, Kang-Pu
1990-01-01
The problem of computing a small vertex separator in a graph arises in the context of computing a good ordering for the parallel factorization of sparse, symmetric matrices. An algebraic approach for computing vertex separators is considered in this paper. It is shown that lower bounds on separator sizes can be obtained in terms of the eigenvalues of the Laplacian matrix associated with a graph. The Laplacian eigenvectors of grid graphs can be computed from Kronecker products involving the eigenvectors of path graphs, and these eigenvectors can be used to compute good separators in grid graphs. A heuristic algorithm is designed to compute a vertex separator in a general graph by first computing an edge separator in the graph from an eigenvector of the Laplacian matrix, and then using a maximum matching in a subgraph to compute the vertex separator. Results on the quality of the separators computed by the spectral algorithm are presented, and these are compared with separators obtained from other algorithms for computing separators. Finally, the time required to compute the Laplacian eigenvector is reported, and the accuracy with which the eigenvector must be computed to obtain good separators is considered. The spectral algorithm has the advantage that it can be implemented on a medium-size multiprocessor in a straightforward manner.
Transformer fault diagnosis using continuous sparse autoencoder.
Wang, Lukun; Zhao, Xiaoying; Pei, Jiangnan; Tang, Gongyou
2016-01-01
This paper proposes a novel continuous sparse autoencoder (CSAE) which can be used in unsupervised feature learning. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. In this paper, CSAE is applied to solve the problem of transformer fault recognition. Firstly, based on dissolved gas analysis method, IEC three ratios are calculated by the concentrations of dissolved gases. Then IEC three ratios data is normalized to reduce data singularity and improve training speed. Secondly, deep belief network is established by two layers of CSAE and one layer of back propagation (BP) network. Thirdly, CSAE is adopted to unsupervised training and getting features. Then BP network is used for supervised training and getting transformer fault. Finally, the experimental data from IEC TC 10 dataset aims to illustrate the effectiveness of the presented approach. Comparative experiments clearly show that CSAE can extract features from the original data, and achieve a superior correct differentiation rate on transformer fault diagnosis.
Index statistical properties of sparse random graphs
NASA Astrophysics Data System (ADS)
Metz, F. L.; Stariolo, Daniel A.
2015-10-01
Using the replica method, we develop an analytical approach to compute the characteristic function for the probability PN(K ,λ ) that a large N ×N adjacency matrix of sparse random graphs has K eigenvalues below a threshold λ . The method allows to determine, in principle, all moments of PN(K ,λ ) , from which the typical sample-to-sample fluctuations can be fully characterized. For random graph models with localized eigenvectors, we show that the index variance scales linearly with N ≫1 for |λ |>0 , with a model-dependent prefactor that can be exactly calculated. Explicit results are discussed for Erdös-Rényi and regular random graphs, both exhibiting a prefactor with a nonmonotonic behavior as a function of λ . These results contrast with rotationally invariant random matrices, where the index variance scales only as lnN , with an universal prefactor that is independent of λ . Numerical diagonalization results confirm the exactness of our approach and, in addition, strongly support the Gaussian nature of the index fluctuations.
Sparse distributed memory prototype: Principles of operation
NASA Technical Reports Server (NTRS)
Flynn, Michael J.; Kanerva, Pentti; Ahanin, Bahram; Bhadkamkar, Neal; Flaherty, Paul; Hickey, Philip
1988-01-01
Sparse distributed memory is a generalized random access memory (RAM) for long binary words. Such words can be written into and read from the memory, and they can be used to address the memory. The main attribute of the memory is sensitivity to similarity, meaning that a word can be read back not only by giving the original right address but also by giving one close to it as measured by the Hamming distance between addresses. Large memories of this kind are expected to have wide use in speech and scene analysis, in signal detection and verification, and in adaptive control of automated equipment. The memory can be realized as a simple, massively parallel computer. Digital technology has reached a point where building large memories is becoming practical. The research is aimed at resolving major design issues that have to be faced in building the memories. The design of a prototype memory with 256-bit addresses and from 8K to 128K locations for 256-bit words is described. A key aspect of the design is extensive use of dynamic RAM and other standard components.
Silicon and tungsten oxide nanostructures for water splitting
NASA Astrophysics Data System (ADS)
Reyes Gil, Karla R.; Spurgeon, Joshua M.; Lewis, Nathan S.
2009-08-01
Inorganic semiconductors are promising materials for driving photoelectrochemical water-splitting reactions. However, there is not a single semiconductor material that can sustain the unassisted splitting of water into H2 and O2. Instead, we are developing a three part cell design where individual catalysts for water reduction and oxidation will be attached to the ends of a membrane. The job of splitting water is therefore divided into separate reduction and oxidation reactions, and each catalyst can be optimized independently for a single reaction. Silicon might be suitable to drive the water reduction. Inexpensive highly ordered Si wire arrays were grown on a single crystal wafer and transferred into a transparent, flexible polymer matrix. In this array, light would be absorbed along the longer axial dimension while the resulting electrons or holes would be collected along the much shorter radial dimension in a massively parallel array resembling carpet fibers on a microscale, hence the term "solar carpet". Tungsten oxide is a good candidate to drive the water oxidation. Self-organized porous tungsten oxide was successfully synthesized on the tungsten foil by anodization. This sponge-like structure absorbs light efficiently due to its high surface area; hence we called it "solar sponge".
Nanoscale Strontium Titanate Photocatalysts for Overall Water Splitting
Townsend, Troy K.; Browning, Nigel D.; Osterloh, Frank
2012-08-28
SrTiO3 (STO) is a large band gap (3.2 eV) semiconductor that catalyzes the overall water splitting reaction under UV light irradiation in the presence of a NiO cocatalyst. As we show here, the reactivity persists in nanoscale particles of the material, although the process is less effective at the nanoscale. To reach these conclusions, Bulk STO, 30 ± 5 nm STO, and 6.5 ± 1 nm STO were synthesized by three different methods, their crystal structures verified with XRD and their morphology observed with HRTEM before and after NiO deposition. In connection with NiO, all samples split water into stoichiometric mixtures of H2 and O2, but the activity is decreasing from 28 μmol H2 g–1 h–1 (bulk STO), to 19.4 μmol H2 g–1 h–1 (30 nm STO), and 3.0 μmol H2 g–1 h–1 (6.5 nm STO). The reasons for this decrease are an increase of the water oxidation overpotential for the smaller particles and reduced light absorption due to a quantum size effect. Overall, these findings establish the first nanoscale titanate photocatalyst for overall water splitting.
Sparsely-Bonded CMOS Hybrid Imager
NASA Technical Reports Server (NTRS)
Cunningham, Thomas J. (Inventor); Hancock, Bruce R. (Inventor); Sun, Chao (Inventor); Jones, Todd J. (Inventor); Dickie, Matthew R. (Inventor); Nikzad, Shouleh (Inventor); Hoenk, Michael E. (Inventor); Wrigley, Christopher J. (Inventor); Newton, Kenneth W. (Inventor); Pain, Bedabrata (Inventor)
2015-01-01
A method and device for imaging or detecting electromagnetic radiation is provided. A device structure includes a first chip interconnected with a second chip. The first chip includes a detector array, wherein the detector array comprises a plurality of light sensors and one or more transistors. The second chip includes a Read Out Integrated Circuit (ROIC) that reads out, via the transistors, a signal produced by the light sensors. A number of interconnects between the ROIC and the detector array can be less than one per light sensor or pixel.
Optimized design and analysis of sparse-sampling FMRI experiments.
Perrachione, Tyler K; Ghosh, Satrajit S
2013-01-01
Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase
New Asteroid Models Based on Combined Dense and Sparse Photometry
NASA Astrophysics Data System (ADS)
Hanuš, Josef; Durech, J.
2010-10-01
For thousands of asteroids we investigated several ten thousands of sparse photometric data from astrometric projects. These data are available on AstDyS server (Asteroids -- Dynamic Site, http://hamilton.dm.unipi.it). We picked 7 astrometric surveys and used their calibrated photometry in lightcurve inversion method for determination of asteroid's convex shapes and rotational states. We present nearly 100 new asteroid models derived from combined dense and sparse data sets, where sparse photometry is taken from AstDyS server and dense lightcurves are from the Uppsala Asteroid Photometric Catalogue (UAPC) and from several individual observers.
Electromagnetic Formation Flight (EMFF) for Sparse Aperture Arrays
NASA Technical Reports Server (NTRS)
Kwon, Daniel W.; Miller, David W.; Sedwick, Raymond J.
2004-01-01
Traditional methods of actuating spacecraft in sparse aperture arrays use propellant as a reaction mass. For formation flying systems, propellant becomes a critical consumable which can be quickly exhausted while maintaining relative orientation. Additional problems posed by propellant include optical contamination, plume impingement, thermal emission, and vibration excitation. For these missions where control of relative degrees of freedom is important, we consider using a system of electromagnets, in concert with reaction wheels, to replace the consumables. Electromagnetic Formation Flight sparse apertures, powered by solar energy, are designed differently from traditional propulsion systems, which are based on V. This paper investigates the design of sparse apertures both inside and outside the Earth's gravity field.
SPARSKIT: A basic tool kit for sparse matrix computations
NASA Technical Reports Server (NTRS)
Saad, Youcef
1990-01-01
Presented here are the main features of a tool package for manipulating and working with sparse matrices. One of the goals of the package is to provide basic tools to facilitate the exchange of software and data between researchers in sparse matrix computations. The starting point is the Harwell/Boeing collection of matrices for which the authors provide a number of tools. Among other things, the package provides programs for converting data structures, printing simple statistics on a matrix, plotting a matrix profile, and performing linear algebra operations with sparse matrices.
Accelerating Dynamic Cardiac MR Imaging Using Structured Sparse Representation
Cai, Nian; Wang, Shengru; Zhu, Shasha
2013-01-01
Compressed sensing (CS) has produced promising results on dynamic cardiac MR imaging by exploiting the sparsity in image series. In this paper, we propose a new method to improve the CS reconstruction for dynamic cardiac MRI based on the theory of structured sparse representation. The proposed method user the PCA subdictionaries for adaptive sparse representation and suppresses the sparse coding noise to obtain good reconstructions. An accelerated iterative shrinkage algorithm is used to solve the optimization problem and achieve a fast convergence rate. Experimental results demonstrate that the proposed method improves the reconstruction quality of dynamic cardiac cine MRI over the state-of-the-art CS method. PMID:24454528
Holographic spectrum-splitting optical systems for solar photovoltaics
NASA Astrophysics Data System (ADS)
Zhang, Deming
Solar energy is the most abundant source of renewable energy available. The relatively high cost prevents solar photovoltaic (PV) from replacing fossil fuel on a larger scale. In solar PV power generation the cost is reduced with more efficient PV technologies. In this dissertation, methods to improve PV conversion efficiency with holographic optical components are discussed. The tandem multiple-junction approach has achieved very high conversion efficiency. However it is impossible to manufacture tandem PV cells at a low cost due to stringent fabrication standards and limited material types that satisfy lattice compatibility. Current produced by the tandem multi-junction PV cell is limited by the lowest junction due to series connection. Spectrum-splitting is a lateral multi-junction concept that is free of lattice and current matching constraints. Each PV cell can be optimized towards full absorption of a spectral band with tailored light-trapping schemes. Holographic optical components are designed to achieve spectrum-splitting PV energy conversion. The incident solar spectrum is separated onto multiple PV cells that are matched to the corresponding spectral band. Holographic spectrum-splitting can take advantage of existing and future low-cost technologies that produces high efficiency thin-film solar cells. Spectrum-splitting optical systems are designed and analyzed with both transmission and reflection holographic optical components. Prototype holograms are fabricated and high optical efficiency is achieved. Light-trapping in PV cells increases the effective optical path-length in the semiconductor material leading to improved absorption and conversion efficiency. It has been shown that the effective optical path length can be increased by a factor of 4n2 using diffusive surfaces. Ultra-light-trapping can be achieved with optical filters that limit the escape angle of the diffused light. Holographic reflection gratings have been shown to act as angle
NASA Astrophysics Data System (ADS)
Shao, Xiaopeng; Li, Huijuan; Wu, Tengfei; Dai, Weijia; Bi, Xiangli
2015-05-01
The incident light will be scattered away due to the inhomogeneity of the refractive index in many materials which will greatly reduce the imaging depth and degrade the imaging quality. Many exciting methods have been presented in recent years for solving this problem and realizing imaging through a highly scattering medium, such as the wavefront modulation technique and reconstruction technique. The imaging method based on compressed sensing (CS) theory can decrease the computational complexity because it doesn't require the whole speckle pattern to realize reconstruction. One of the key premises of this method is that the object is sparse or can be sparse representation. However, choosing a proper projection matrix is very important to the imaging quality. In this paper, we analyzed that the transmission matrix (TM) of a scattering medium obeys circular Gaussian distribution, which makes it possible that a scattering medium can be used as the measurement matrix in the CS theory. In order to verify the performance of this method, a whole optical system is simulated. Various projection matrices are introduced to make the object sparse, including the fast Fourier transform (FFT) basis, the discrete cosine transform (DCT) basis and the discrete wavelet transform (DWT) basis, the imaging performances of each of which are compared comprehensively. Simulation results show that for most targets, applying the discrete wavelet transform basis will obtain an image in good quality. This work can be applied to biomedical imaging and used to develop real-time imaging through highly scattering media.
Wiring of Photosystem II to Hydrogenase for Photoelectrochemical Water Splitting.
Mersch, Dirk; Lee, Chong-Yong; Zhang, Jenny Zhenqi; Brinkert, Katharina; Fontecilla-Camps, Juan C; Rutherford, A William; Reisner, Erwin
2015-07-01
In natural photosynthesis, light is used for the production of chemical energy carriers to fuel biological activity. The re-engineering of natural photosynthetic pathways can provide inspiration for sustainable fuel production and insights for understanding the process itself. Here, we employ a semiartificial approach to study photobiological water splitting via a pathway unavailable to nature: the direct coupling of the water oxidation enzyme, photosystem II, to the H2 evolving enzyme, hydrogenase. Essential to this approach is the integration of the isolated enzymes into the artificial circuit of a photoelectrochemical cell. We therefore developed a tailor-made hierarchically structured indium-tin oxide electrode that gives rise to the excellent integration of both photosystem II and hydrogenase for performing the anodic and cathodic half-reactions, respectively. When connected together with the aid of an applied bias, the semiartificial cell demonstrated quantitative electron flow from photosystem II to the hydrogenase with the production of H2 and O2 being in the expected two-to-one ratio and a light-to-hydrogen conversion efficiency of 5.4% under low-intensity red-light irradiation. We thereby demonstrate efficient light-driven water splitting using a pathway inaccessible to biology and report on a widely applicable in vitro platform for the controlled coupling of enzymatic redox processes to meaningfully study photocatalytic reactions.
Split liver transplantation in adults.
Hashimoto, Koji; Fujiki, Masato; Quintini, Cristiano; Aucejo, Federico N; Uso, Teresa Diago; Kelly, Dympna M; Eghtesad, Bijan; Fung, John J; Miller, Charles M
2016-09-01
Split liver transplantation (SLT), while widely accepted in pediatrics, remains underutilized in adults. Advancements in surgical techniques and donor-recipient matching, however, have allowed expansion of SLT from utilization of the right trisegment graft to now include use of the hemiliver graft as well. Despite less favorable outcomes in the early experience, better outcomes have been reported by experienced centers and have further validated the feasibility of SLT. Importantly, more than two decades of experience have identified key requirements for successful SLT in adults. When these requirements are met, SLT can achieve outcomes equivalent to those achieved with other types of liver transplantation for adults. However, substantial challenges, such as surgical techniques, logistics, and ethics, persist as ongoing barriers to further expansion of this highly complex procedure. This review outlines the current state of SLT in adults, focusing on donor and recipient selection based on physiology, surgical techniques, surgical outcomes, and ethical issues. PMID:27672272
Salt splitting with ceramic membranes
Kurath, D.
1996-10-01
The purpose of this task is to develop ceramic membrane technologies for salt splitting of radioactively contaminated sodium salt solutions. This technology has the potential to reduce the low-level waste (LLW) disposal volume, the pH and sodium hydroxide content for subsequent processing steps, the sodium content of interstitial liquid in high-level waste (HLW) sludges, and provide sodium hydroxide free of aluminum for recycle within processing plants at the DOE complex. Potential deployment sites include Hanford, Savannah River, and Idaho National Engineering Laboratory (INEL). The technical approach consists of electrochemical separation of sodium ions from the salt solution using sodium (Na) Super Ion Conductors (NaSICON). As the name implies, sodium ions are transported rapidly through these ceramic crystals even at room temperatures.
NASA Astrophysics Data System (ADS)
Cohen, Timothy; Craig, Nathaniel; Knapen, Simon
2016-03-01
We propose a simple model of split supersymmetry from gauge mediation. This model features gauginos that are parametrically a loop factor lighter than scalars, accommodates a Higgs boson mass of 125 GeV, and incorporates a simple solution to the μ- b μ problem. The gaugino mass suppression can be understood as resulting from collective symmetry breaking. Imposing collider bounds on μ and requiring viable electroweak symmetry breaking implies small a-terms and small tan β — the stop mass ranges from 105 to 108 GeV. In contrast with models with anomaly + gravity mediation (which also predict a one-loop loop suppression for gaugino masses), our gauge mediated scenario predicts aligned squark masses and a gravitino LSP. Gluinos, electroweakinos and Higgsinos can be accessible at the LHC and/or future colliders for a wide region of the allowed parameter space.
NASA Astrophysics Data System (ADS)
Kusenko, Alexander; Takahashi, Fuminobu; Yanagida, Tsutomu T.
2010-09-01
The seesaw mechanism in models with extra dimensions is shown to be generically consistent with a broad range of Majorana masses. The resulting democracy of scales implies that the seesaw mechanism can naturally explain the smallness of neutrino masses for an arbitrarily small right-handed neutrino mass. If the scales of the seesaw parameters are split, with two right-handed neutrinos at a high scale and one at a keV scale, one can explain the matter-antimatter asymmetry of the universe, as well as dark matter. The dark matter candidate, a sterile right-handed neutrino with mass of several keV, can account for the observed pulsar velocities and for the recent data from Chandra X-ray Observatory, which suggest the existence of a 5 keV sterile right-handed neutrino.
Split liver transplantation in adults
Hashimoto, Koji; Fujiki, Masato; Quintini, Cristiano; Aucejo, Federico N; Uso, Teresa Diago; Kelly, Dympna M; Eghtesad, Bijan; Fung, John J; Miller, Charles M
2016-01-01
Split liver transplantation (SLT), while widely accepted in pediatrics, remains underutilized in adults. Advancements in surgical techniques and donor-recipient matching, however, have allowed expansion of SLT from utilization of the right trisegment graft to now include use of the hemiliver graft as well. Despite less favorable outcomes in the early experience, better outcomes have been reported by experienced centers and have further validated the feasibility of SLT. Importantly, more than two decades of experience have identified key requirements for successful SLT in adults. When these requirements are met, SLT can achieve outcomes equivalent to those achieved with other types of liver transplantation for adults. However, substantial challenges, such as surgical techniques, logistics, and ethics, persist as ongoing barriers to further expansion of this highly complex procedure. This review outlines the current state of SLT in adults, focusing on donor and recipient selection based on physiology, surgical techniques, surgical outcomes, and ethical issues.
Split liver transplantation in adults
Hashimoto, Koji; Fujiki, Masato; Quintini, Cristiano; Aucejo, Federico N; Uso, Teresa Diago; Kelly, Dympna M; Eghtesad, Bijan; Fung, John J; Miller, Charles M
2016-01-01
Split liver transplantation (SLT), while widely accepted in pediatrics, remains underutilized in adults. Advancements in surgical techniques and donor-recipient matching, however, have allowed expansion of SLT from utilization of the right trisegment graft to now include use of the hemiliver graft as well. Despite less favorable outcomes in the early experience, better outcomes have been reported by experienced centers and have further validated the feasibility of SLT. Importantly, more than two decades of experience have identified key requirements for successful SLT in adults. When these requirements are met, SLT can achieve outcomes equivalent to those achieved with other types of liver transplantation for adults. However, substantial challenges, such as surgical techniques, logistics, and ethics, persist as ongoing barriers to further expansion of this highly complex procedure. This review outlines the current state of SLT in adults, focusing on donor and recipient selection based on physiology, surgical techniques, surgical outcomes, and ethical issues. PMID:27672272
Dephasing in coherently split quasicondensates
Stimming, H.-P.; Mauser, N. J.; Mazets, I. E.
2011-02-15
We numerically model the evolution of a pair of coherently split quasicondensates. A truly one-dimensional case is assumed, so that the loss of the (initially high) coherence between the two quasicondensates is due to dephasing only, but not due to the violation of integrability and subsequent thermalization (which are excluded from the present model). We confirm the subexponential time evolution of the coherence between two quasicondensates {proportional_to}exp[-(t/t{sub 0}){sup 2/3}], experimentally observed by Hofferberth et al. [Nature 449, 324 (2007)]. The characteristic time t{sub 0} is found to scale as the square of the ratio of the linear density of a quasicondensate to its temperature, and we analyze the full distribution function of the interference contrast and the decay of the phase correlation.
Split liver transplantation in adults.
Hashimoto, Koji; Fujiki, Masato; Quintini, Cristiano; Aucejo, Federico N; Uso, Teresa Diago; Kelly, Dympna M; Eghtesad, Bijan; Fung, John J; Miller, Charles M
2016-09-01
Split liver transplantation (SLT), while widely accepted in pediatrics, remains underutilized in adults. Advancements in surgical techniques and donor-recipient matching, however, have allowed expansion of SLT from utilization of the right trisegment graft to now include use of the hemiliver graft as well. Despite less favorable outcomes in the early experience, better outcomes have been reported by experienced centers and have further validated the feasibility of SLT. Importantly, more than two decades of experience have identified key requirements for successful SLT in adults. When these requirements are met, SLT can achieve outcomes equivalent to those achieved with other types of liver transplantation for adults. However, substantial challenges, such as surgical techniques, logistics, and ethics, persist as ongoing barriers to further expansion of this highly complex procedure. This review outlines the current state of SLT in adults, focusing on donor and recipient selection based on physiology, surgical techniques, surgical outcomes, and ethical issues.
Split Immunological Tolerance to Trophoblast
de Mestre, Amanda; Noronha, Leela; Wagner, Bettina; Antczak, Douglas F.
2010-01-01
Split immunological tolerance refers to states in which an individual is capable of mounting certain types of immune responses to a particular antigenic challenge, but is tolerant of the same antigen in other compartments of the immune system. This concept is applicable to the immunological relationship between mother and fetus, and particularly relevant in equine pregnancy. In pregnant mares, antibody responses to paternal foreign Major Histocompatibility Complex class I antigens are robust, while anti-paternal cytotoxic T cell responses are diminished compared to those mounted by non-pregnant mares. Here we compared the distribution of the major lymphocyte subsets, the percentage of lymphocytes expressing Interferon Gamma (IFNG) and Interleukin 4 (IL4) and the level of expression of the immunoregulatory transcription factor FOXP3 between pregnant and non-pregnant mares, and between peripheral blood and the endometrium during pregnancy. In a cohort of mares in which peripheral blood lymphocytes were tested during early pregnancy and in the non-pregnant state, there were only slight changes observed during pregnancy. In contrast, comparison of peripheral blood lymphocytes with lymphocytes isolated from the endometrial cups of pregnant mares revealed striking differences in lymphocyte sub-populations. The endometrial cups contained higher numbers of IFNG+ lymphocytes, and lower numbers of lymphocytes expressing IL4. The endometrial cup lymphocytes also had higher numbers of FOXP3+ cells compared to peripheral blood lymphocytes. Taken together, these results strengthen the evidence for a state of split tolerance to trophoblast, and furthermore define sharp differences in immune reactivity during equine pregnancy between peripheral blood lymphocytes and lymphocytes at the maternal-fetal interface. PMID:19876828
Salt splitting using ceramic membranes
Kurath, D.E.
1997-10-01
Many radioactive aqueous wastes in the DOE complex have high concentrations of sodium that can negatively affect waste treatment and disposal operations. Sodium can decrease the durability of waste forms such as glass and is the primary contributor to large disposal volumes. Waste treatment processes such as cesium ion exchange, sludge washing, and calcination are made less efficient and more expensive because of the high sodium concentrations. Pacific Northwest National Laboratory (PNNL) and Ceramatec Inc. (Salt Lake City UT) are developing an electrochemical salt splitting process based on inorganic ceramic sodium (Na), super-ionic conductor (NaSICON) membranes that shows promise for mitigating the impact of sodium. In this process, the waste is added to the anode compartment, and an electrical potential is applied to the cell. This drives sodium ions through the membrane, but the membrane rejects most other cations (e.g., Sr{sup +2}, Cs{sup +}). The charge balance in the anode compartment is maintained by generating H{sup +} from the electrolysis of water. The charge balance in the cathode is maintained by generating OH{sup {minus}}, either from the electrolysis of water or from oxygen and water using an oxygen cathode. The normal gaseous products of the electrolysis of water are oxygen at the anode and hydrogen at the cathode. Potentially flammable gas mixtures can be prevented by providing adequate volumes of a sweep gas, using an alternative reductant or destruction of the hydrogen as it is generated. As H{sup +} is generated in the anode compartment, the pH drops. The process may be operated with either an alkaline (pH>12) or an acidic anolyte (pH <1). The benefits of salt splitting using ceramic membranes are (1) waste volume reduction and reduced chemical procurement costs by recycling of NaOH; and (2) direct reduction of sodium in process streams, which enhances subsequent operations such as cesium ion exchange, calcination, and vitrification.
Maverick Comet Splits during Dramatic Outburst
NASA Astrophysics Data System (ADS)
1996-01-01
magnitude 13, quite normal for this comet at the given heliocentric distance. This corresponds to about 700 times fainter than what can be seen with the unaided eye. However, on September 8-12, Jacques Crovisier and his colleagues from the Paris Observatory (Meudon) used the large Nancay radiotelescope to determine the amount of hydroxyle molecules (OH) around SW-3. To their great surprise, they found that it was much larger than predicted. Their careful measurements showed beyond any doubt that SW-3 was emitting enormous amounts of water (H2O), the ``parent'' molecule from which OH is produced by dissociation. Subsequent visual observations by amateur astronomers all over the world confirmed that a dramatic outburst was in progress; on September 17, the comet was recorded at magnitude 8, or 100 times brighter than expected. The overall intensity kept increasing until mid-October, when the magnitude was brighter than 6, or nearly 1000 times brighter than expected, and the comet was in principle visible to the naked eye from dark sites. Only a few comets have ever experienced such an enormous, unexpected increase in brightness. At that time, SW-3 had just passed its perihelion and was ``crossing'' the Earth's orbit on its way out. The distance to the Earth was close to 200 million kilometres. The Observations at ESO It was therefore with particular expectations that the two astronomers went to their respectively ESO telescopes on December 12-14, 1995, to observe SW-3. Although the comet at this time had become about 5 times fainter than when it was brightest, they still hoped that their observations would be able to cast some light on its very peculiar behaviour. And indeed, thanks to the very good image quality, both the EMMI and TIMMI instruments immediately and for the first time showed that the nucleus of SW-3 had split. On the CCD images from EMMI, three distinct light condensations were visible, well aligned with the two outermost at an angular distance of 4
Solar photochemical and thermochemical splitting of water.
Rao, C N R; Lingampalli, S R; Dey, Sunita; Roy, Anand
2016-02-28
Artificial photosynthesis to carry out both the oxidation and the reduction of water has emerged to be an exciting area of research. It has been possible to photochemically generate oxygen by using a scheme similar to the Z-scheme, by using suitable catalysts in place of water-oxidation catalyst in the Z-scheme in natural photosynthesis. The best oxidation catalysts are found to be Co and Mn oxides with the e(1) g configuration. The more important aspects investigated pertain to the visible-light-induced generation of hydrogen by using semiconductor heterostructures of the type ZnO/Pt/Cd1-xZnxS and dye-sensitized semiconductors. In the case of heterostructures, good yields of H2 have been obtained. Modifications of the heterostructures, wherein Pt is replaced by NiO, and the oxide is substituted with different anions are discussed. MoS2 and MoSe2 in the 1T form yield high quantities of H2 when sensitized by Eosin Y. Two-step thermochemical splitting of H2O using metal oxide redox pairs provides a strategy to produce H2 and CO. Performance of the Ln0.5A0.5MnO3 (Ln = rare earth ion, A = Ca, Sr) family of perovskites is found to be promising in this context. The best results to date are found with Y0.5Sr0.5MnO3. PMID:26755752
Solar photochemical and thermochemical splitting of water.
Rao, C N R; Lingampalli, S R; Dey, Sunita; Roy, Anand
2016-02-28
Artificial photosynthesis to carry out both the oxidation and the reduction of water has emerged to be an exciting area of research. It has been possible to photochemically generate oxygen by using a scheme similar to the Z-scheme, by using suitable catalysts in place of water-oxidation catalyst in the Z-scheme in natural photosynthesis. The best oxidation catalysts are found to be Co and Mn oxides with the e(1) g configuration. The more important aspects investigated pertain to the visible-light-induced generation of hydrogen by using semiconductor heterostructures of the type ZnO/Pt/Cd1-xZnxS and dye-sensitized semiconductors. In the case of heterostructures, good yields of H2 have been obtained. Modifications of the heterostructures, wherein Pt is replaced by NiO, and the oxide is substituted with different anions are discussed. MoS2 and MoSe2 in the 1T form yield high quantities of H2 when sensitized by Eosin Y. Two-step thermochemical splitting of H2O using metal oxide redox pairs provides a strategy to produce H2 and CO. Performance of the Ln0.5A0.5MnO3 (Ln = rare earth ion, A = Ca, Sr) family of perovskites is found to be promising in this context. The best results to date are found with Y0.5Sr0.5MnO3.
Generation of high-power laser light with Gigahertz splitting.
Unks, B E; Proite, N A; Yavuz, D D
2007-08-01
We demonstrate the generation of two high-power laser beams whose frequencies are separated by the ground state hyperfine transition frequency in (87)Rb. The system uses a single master diode laser appropriately shifted by high frequency acousto-optic modulators and amplified by semiconductor tapered amplifiers. This produces two 1 W laser beams with a frequency spacing of 6.834 GHz and a relative frequency stability of 1 Hz. We discuss possible applications of this apparatus, including electromagnetically induced transparency-like effects and ultrafast qubit rotations. PMID:17764314
Finding One Community in a Sparse Graph
NASA Astrophysics Data System (ADS)
Montanari, Andrea
2015-10-01
We consider a random sparse graph with bounded average degree, in which a subset of vertices has higher connectivity than the background. In particular, the average degree inside this subset of vertices is larger than outside (but still bounded). Given a realization of such graph, we aim at identifying the hidden subset of vertices. This can be regarded as a model for the problem of finding a tightly knitted community in a social network, or a cluster in a relational dataset. In this paper we present two sets of contributions: ( i) We use the cavity method from spin glass theory to derive an exact phase diagram for the reconstruction problem. In particular, as the difference in edge probability increases, the problem undergoes two phase transitions, a static phase transition and a dynamic one. ( ii) We establish rigorous bounds on the dynamic phase transition and prove that, above a certain threshold, a local algorithm (belief propagation) correctly identify most of the hidden set. Below the same threshold no local algorithm can achieve this goal. However, in this regime the subset can be identified by exhaustive search. For small hidden sets and large average degree, the phase transition for local algorithms takes an intriguingly simple form. Local algorithms succeed with high probability for deg _in - deg _out > √{deg _out/e} and fail for deg _in - deg _out < √{deg _out/e} (with deg _in, deg _out the average degrees inside and outside the community). We argue that spectral algorithms are also ineffective in the latter regime. It is an open problem whether any polynomial time algorithms might succeed for deg _in - deg _out < √{deg _out/e}.
Sparse source configurations for asteroid tomography
NASA Astrophysics Data System (ADS)
Pursiainen, S.; Kaasalainen, M.
2014-04-01
The objective of our recent research has been to develop non-invasive imaging techniques for future planetary research and mining activities involving a challenging in situ environment and tight payload limits [1]. This presentation will deal in particular with an approach in which the internal relative permittivity ∈r or the refractive index n = √ ∈r of an asteroid is to be recovered based on radio signal transmitted by a sparse set [2] of fixed or movable landers. To address important aspects of mission planning, we have analyzed different signal source configurations to find the minimal number of source positions needed for robust localization of anomalies, such as internal voids. Characteristic to this inverse problem are the large relative changes in signal speed caused by the high permittivity of typical asteroid minerals (e.g. basalt), leading to strong refractions and reflections of the signal. Finding an appropriate problemspecific signaling arrangement is an important premission goal for successful in situ measurements. This presentation will include inversion results obtained with laboratory-recorded travel time data y of the form in which n δ denotes a perturbation of a refractive index n = n δ + nbg; gi estimates the total noise due to different error sources; (ybg)i = ∫Ci nbg ds is an entry of noiseless background data ybg; and Ci is a signal path. Also simulated time-evolution data will be covered with respect to potential u satisfying the wave equation ∈rδ2/δt2+ ōδu/δt-∆u = f, where ō is a (latent) conductivity distribution and f is a source term. Special interest will be paid to inversion robustness regarding changes of the prior model and source positioning. Among other things, our analysis suggests that strongly refractive anomalies can be detected with three or four sources independently of their positioning.
Effects of neuromuscular function and split step on reaction speed in simulated tennis response.
Nieminen, Marko J J; Piirainen, Jarmo M; Salmi, Jukka A; Linnamo, Vesa
2014-01-01
The purpose of this study was to examine whether split step (small hop before step) would be more beneficial than no-split condition in simulated tennis response situation. In addition, it was studied if movement time of the response is related to separately measured force production capabilities and reflex sensitivity of the players. Nine skilled male tennis players participated in this study. Subjects stood on a force plate and reacted to a light signal and moved to appointed direction as fast as possible. With split step the participants were 13.1% faster (P <0.05) than without split step from the start to the distal end of the so called close range movement continuum (2.70 m). This was mainly explained by 43.6% faster time (P <0.05) from the signal to the onset of force production. Greater vertical forces were observed with split step: 15.7% greater F(z) mean force (P <0.05), 60.0% greater F(z) peak force (P<0.01). In split step both mean (r= - 0.813, P <0.01) and peak (r=-0.765, P <0.05) vertical forces (Fz) correlated negatively with the time from the onset of the force production to the photocell. With split step higher EMGs were observed in muscles responsible for ankle joint movement indicating that different strategies were used. Due to the split step the players were able to start the movement faster which mostly explains the advantages over the no-split step condition. Split step condition may also benefit from stretch shortening type of muscle action.
Multiple kernel learning for sparse representation-based classification.
Shrivastava, Ashish; Patel, Vishal M; Chellappa, Rama
2014-07-01
In this paper, we propose a multiple kernel learning (MKL) algorithm that is based on the sparse representation-based classification (SRC) method. Taking advantage of the nonlinear kernel SRC in efficiently representing the nonlinearities in the high-dimensional feature space, we propose an MKL method based on the kernel alignment criteria. Our method uses a two step training method to learn the kernel weights and sparse codes. At each iteration, the sparse codes are updated first while fixing the kernel mixing coefficients, and then the kernel mixing coefficients are updated while fixing the sparse codes. These two steps are repeated until a stopping criteria is met. The effectiveness of the proposed method is demonstrated using several publicly available image classification databases and it is shown that this method can perform significantly better than many competitive image classification algorithms. PMID:24835226
Ensemble polarimetric SAR image classification based on contextual sparse representation
NASA Astrophysics Data System (ADS)
Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun
2016-05-01
Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.
STIS Sparse Field CTE test-internal {Cycle 12}
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
2003-07-01
CTE measurements are made using the "internal sparse field test", along the parallel axis. The "POS=" optional parameter, introduced during cycle 11, is used to provide off-center MSM positionings of some slits. All exposures are internals.
STIS Sparse Field CTE test-internal {Cycle 11}
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
2002-07-01
CTE measurements are made using the "internal sparse field test", along the parallel axis. The new "POS=" optional parameter is used to provide off-center MSM positionings of some slits. All exposures are internals.
Tang, Xin; Feng, Guo-can; Li, Xiao-xin; Cai, Jia-xin
2015-01-01
Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the
Tang, Xin; Feng, Guo-Can; Li, Xiao-Xin; Cai, Jia-Xin
2015-01-01
Face recognition is challenging especially when the images from different persons are similar to each other due to variations in illumination, expression, and occlusion. If we have sufficient training images of each person which can span the facial variations of that person under testing conditions, sparse representation based classification (SRC) achieves very promising results. However, in many applications, face recognition often encounters the small sample size problem arising from the small number of available training images for each person. In this paper, we present a novel face recognition framework by utilizing low-rank and sparse error matrix decomposition, and sparse coding techniques (LRSE+SC). Firstly, the low-rank matrix recovery technique is applied to decompose the face images per class into a low-rank matrix and a sparse error matrix. The low-rank matrix of each individual is a class-specific dictionary and it captures the discriminative feature of this individual. The sparse error matrix represents the intra-class variations, such as illumination, expression changes. Secondly, we combine the low-rank part (representative basis) of each person into a supervised dictionary and integrate all the sparse error matrix of each individual into a within-individual variant dictionary which can be applied to represent the possible variations between the testing and training images. Then these two dictionaries are used to code the query image. The within-individual variant dictionary can be shared by all the subjects and only contribute to explain the lighting conditions, expressions, and occlusions of the query image rather than discrimination. At last, a reconstruction-based scheme is adopted for face recognition. Since the within-individual dictionary is introduced, LRSE+SC can handle the problem of the corrupted training data and the situation that not all subjects have enough samples for training. Experimental results show that our method achieves the
Testing of Error-Correcting Sparse Permutation Channel Codes
NASA Technical Reports Server (NTRS)
Shcheglov, Kirill, V.; Orlov, Sergei S.
2008-01-01
A computer program performs Monte Carlo direct numerical simulations for testing sparse permutation channel codes, which offer strong error-correction capabilities at high code rates and are considered especially suitable for storage of digital data in holographic and volume memories. A word in a code of this type is characterized by, among other things, a sparseness parameter (M) and a fixed number (K) of 1 or "on" bits in a channel block length of N.
Out-of-Core Solutions of Complex Sparse Linear Equations
NASA Technical Reports Server (NTRS)
Yip, E. L.
1982-01-01
ETCLIB is library of subroutines for obtaining out-of-core solutions of complex sparse linear equations. Routines apply to dense and sparse matrices too large to be stored in core. Useful for solving any set of linear equations, but particularly useful in cases where coefficient matrix has no special properties that guarantee convergence with any of interative processes. The only assumption made is that coefficient matrix is not singular.
Saliency Detection Using Sparse and Nonlinear Feature Representation
Zhao, Qingjie; Manzoor, Muhammad Farhan; Ishaq Khan, Saqib
2014-01-01
An important aspect of visual saliency detection is how features that form an input image are represented. A popular theory supports sparse feature representation, an image being represented with a basis dictionary having sparse weighting coefficient. Another method uses a nonlinear combination of image features for representation. In our work, we combine the two methods and propose a scheme that takes advantage of both sparse and nonlinear feature representation. To this end, we use independent component analysis (ICA) and covariant matrices, respectively. To compute saliency, we use a biologically plausible center surround difference (CSD) mechanism. Our sparse features are adaptive in nature; the ICA basis function are learnt at every image representation, rather than being fixed. We show that Adaptive Sparse Features when used with a CSD mechanism yield better results compared to fixed sparse representations. We also show that covariant matrices consisting of nonlinear integration of color information alone are sufficient to efficiently estimate saliency from an image. The proposed dual representation scheme is then evaluated against human eye fixation prediction, response to psychological patterns, and salient object detection on well-known datasets. We conclude that having two forms of representation compliments one another and results in better saliency detection. PMID:24895644
Vector sparse representation of color image using quaternion matrix analysis.
Xu, Yi; Yu, Licheng; Xu, Hongteng; Zhang, Hao; Nguyen, Truong
2015-04-01
Traditional sparse image models treat color image pixel as a scalar, which represents color channels separately or concatenate color channels as a monochrome image. In this paper, we propose a vector sparse representation model for color images using quaternion matrix analysis. As a new tool for color image representation, its potential applications in several image-processing tasks are presented, including color image reconstruction, denoising, inpainting, and super-resolution. The proposed model represents the color image as a quaternion matrix, where a quaternion-based dictionary learning algorithm is presented using the K-quaternion singular value decomposition (QSVD) (generalized K-means clustering for QSVD) method. It conducts the sparse basis selection in quaternion space, which uniformly transforms the channel images to an orthogonal color space. In this new color space, it is significant that the inherent color structures can be completely preserved during vector reconstruction. Moreover, the proposed sparse model is more efficient comparing with the current sparse models for image restoration tasks due to lower redundancy between the atoms of different color channels. The experimental results demonstrate that the proposed sparse image model avoids the hue bias issue successfully and shows its potential as a general and powerful tool in color image analysis and processing domain. PMID:25643407
Visual tracking based on extreme learning machine and sparse representation.
Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen
2015-01-01
The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359
Representation-Independent Iteration of Sparse Data Arrays
NASA Technical Reports Server (NTRS)
James, Mark
2007-01-01
An approach is defined that describes a method of iterating over massively large arrays containing sparse data using an approach that is implementation independent of how the contents of the sparse arrays are laid out in memory. What is unique and important here is the decoupling of the iteration over the sparse set of array elements from how they are internally represented in memory. This enables this approach to be backward compatible with existing schemes for representing sparse arrays as well as new approaches. What is novel here is a new approach for efficiently iterating over sparse arrays that is independent of the underlying memory layout representation of the array. A functional interface is defined for implementing sparse arrays in any modern programming language with a particular focus for the Chapel programming language. Examples are provided that show the translation of a loop that computes a matrix vector product into this representation for both the distributed and not-distributed cases. This work is directly applicable to NASA and its High Productivity Computing Systems (HPCS) program that JPL and our current program are engaged in. The goal of this program is to create powerful, scalable, and economically viable high-powered computer systems suitable for use in national security and industry by 2010. This is important to NASA for its computationally intensive requirements for analyzing and understanding the volumes of science data from our returned missions.
Visual Tracking Based on Extreme Learning Machine and Sparse Representation
Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen
2015-01-01
The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker. PMID:26506359
Automatic target recognition using group-structured sparse representation
NASA Astrophysics Data System (ADS)
Sun, Bo; Wu, Xuewen; He, Jun; Zhu, Xiaoming; Chen, Chao
2014-06-01
Sparse representation classification method has been increasingly used in the fields of computer vision and pattern analysis, due to its high recognition rate, little dependence on the features, robustness to corruption and occlusion, and etc. However, most of these existing methods aim to find the sparsest representations of the test sample y in an overcomplete dictionary, which do not particularly consider the relevant structure between the atoms in the dictionary. Moreover, sufficient training samples are always required by the sparse representation method for effective recognition. In this paper we formulate the classification as a group-structured sparse representation problem using a sparsity-inducing norm minimization optimization and propose a novel sparse representation-based automatic target recognition (ATR) framework for the practical applications in which the training samples are drawn from the simulation models of real targets. The experimental results show that the proposed approach improves the recognition rate of standard sparse models, and our system can effectively and efficiently recognize targets under real environments, especially, where the good characteristics of the sparse representation based classification method are kept.
The master patient index: split patient records.
Wieners, W; Stewart, S P
1988-11-01
Systems integrators have overlooked the potential for corrupting the medical-record database through the creation of multiple (split) records for the individual patient. This article introduces a computer software technology that has been used at the University of California, San Francisco (UCSF) Medical Center to identify split patient records.
Precision aligned split V-block
George, Irwin S.
1984-01-01
A precision aligned split V-block for holding a workpiece during a milling operation having an expandable frame for allowing various sized workpieces to be accommodated, is easily secured directly to the mill table and having key lugs in one base of the split V-block that assures constant alignment.
Splitting and Projection at Work in Schools
ERIC Educational Resources Information Center
Dunning, Gerald; James, Chris; Jones, Nicola
2005-01-01
Purpose: The purpose of this paper is to report research into the social defence of splitting and projection in schools. In splitting and projection, organisational members separate their unbearable feelings from the more acceptable ones and project them, typically towards other individuals and groups. Design/methodology/approach: The research was…
Transferring Goods or Splitting a Resource Pool
ERIC Educational Resources Information Center
Dijkstra, Jacob; Van Assen, Marcel A. L. M.
2008-01-01
We investigated the consequences for exchange outcomes of the violation of an assumption underlying most social psychological research on exchange. This assumption is that the negotiated direct exchange of commodities between two actors (pure exchange) can be validly represented as two actors splitting a fixed pool of resources (split pool…
Cheating More when the Spoils Are Split
ERIC Educational Resources Information Center
Wiltermuth, Scott S.
2011-01-01
Four experiments demonstrated that people are more likely to cheat when the benefits of doing so are split with another person, even an anonymous stranger, than when the actor alone captures all of the benefits. In three of the studies, splitting the benefits of over-reporting one's performance on a task made such over-reporting seem less…
Sparse but specific temporal coding by spikes in an insect sensory-motor ocellar pathway.
Simmons, Peter J; van Steveninck, Rob R de Ruyter
2010-08-01
We investigate coding in a locust brain neuron, DNI, which transforms graded synaptic input from ocellar L-neurons into axonal spikes that travel to excite particular thoracic flight neurons. Ocellar neurons are naturally stimulated by fluctuations in light collected from a wide field of view, for example when the visual horizon moves up and down. We used two types of stimuli: fluctuating light from a light-emitting diode (LED), and a visual horizon displayed on an electrostatic monitor. In response to randomly fluctuating light stimuli delivered from the LED, individual spikes in DNI occur sparsely but are timed to sub-millisecond precision, carrying substantial information: 4.5-7 bits per spike in our experiments. In response to these light stimuli, the graded potential signal in DNI carries considerably less information than in presynaptic L-neurons. DNI is excited in phase with either sinusoidal light from an LED or a visual horizon oscillating up and down at 20 Hz, and changes in mean light level or mean horizon level alter the timing of excitation for each cycle. DNI is a multimodal interneuron, but its ability to time spikes precisely in response to ocellar stimulation is not degraded by additional excitation. We suggest that DNI is part of an optical proprioceptor system, responding to the optical signal induced in the ocelli by nodding movements of the locust head during each wing-beat. PMID:20639424
Hyperfine meson splittings: chiral symmetry versus transverse gluon exchange
Felipe J. Llanes-Estrada; Stephen R. Cotanch; Adam P. Szczepaniak; Eric S. Swanson
2004-02-01
Meson spin splittings are examined within an effective Coulomb gauge QCD Hamiltonian incorporating chiral symmetry and a transverse hyperfine interaction necessary for heavy quarks. For light and heavy quarkonium systems the pseudoscalar-vector meson spectrum is generated by approximate BCS-RPA diagonalizations. This relativistic formulation includes both S and D waves for the vector mesons which generates a set of coupled integral equations. A smooth transition from the heavy to the light quark regime is found with chiral symmetry dominating the /pi-/rho mass difference. A good, consistent description of the observed meson spin splittings and chiral quantities, such as the quark condensate and the /pi mass, is obtained. Similar comparisons with TDA diagonalizations, which violate chiral symmetry, are deficient for light pseudoscalar mesons indicating the need to simultaneously include both chiral symmetry and a hyperfine interaction. The /eta{sub b} mass is predicted to be around 9400 MeV consistent with other theoretical expectations and above the unconfirmed 9300 MeV candidate. Finally, for comparison with lattice results, the J reliability parameter is also evaluated.
Unveiling the photonic spin Hall effect with asymmetric spin-dependent splitting.
Zhou, Xinxing; Ling, Xiaohui
2016-02-01
The photonic spin Hall effect (SHE) manifests itself as the spin-dependent splitting of light beam. Usually, it shows a symmetric spin-dependent splitting, i.e., the left- and right-handed circularly polarized components are equally separated in position and intensity for linear polarization incidence. In this paper, we theoretically propose an asymmetric spin-dependent splitting at an air-glass interface under the illumination of elliptical polarization beam and experimentally demonstrate it with the weak measurement method. The left- and right-handed circularly polarized components show expectedly unequal intensity distributions and unexpectedly different spin-dependent shifts. Remarkably, the asymmetric spin-dependent splitting can be modulated by adjusting the handedness of incident polarization. The inherent physics behind this interesting phenomenon is attributed to the additional spatial Imbert-Fedorov shift. These findings offer us potential methods for developing new spin-based nanophotonic applications. PMID:26906868
Lightweight electrical connector split backshell
NASA Technical Reports Server (NTRS)
Goldman, Elliot (Inventor)
2009-01-01
An electrical connector split backshell is provided, comprising two substantially identical backshell halves. Each half includes a first side and a cam projecting therefrom along an axis perpendicular thereto, the cam having an alignment tooth with a constant radius and an engagement section with a radius that increases with angular distance from the alignment tooth. Each half further includes a second side parallel to the first side and a circular sector opening disposed in the second side, the circular sector opening including an inner surface configured as a ramp with a constant radius, the ramp being configured to engage with an engagement section of a cam of the other half, the circular sector opening further including a relieved pocket configured to receive an alignment tooth of the cam of the other half. Each half further includes a back side perpendicular to the first and second sides and a wire bundle notch disposed in the back side, the wire bundle notch configured to align with a wire bundle notch of the other half to form a wire bundle opening. The two substantially identical halves are rotatably coupled by engaging the engagement section of each half to the ramp of the other half.
Innovative solar thermochemical water splitting.
Hogan, Roy E. Jr.; Siegel, Nathan P.; Evans, Lindsey R.; Moss, Timothy A.; Stuecker, John Nicholas; Diver, Richard B., Jr.; Miller, James Edward; Allendorf, Mark D.; James, Darryl L.
2008-02-01
Sandia National Laboratories (SNL) is evaluating the potential of an innovative approach for splitting water into hydrogen and oxygen using two-step thermochemical cycles. Thermochemical cycles are heat engines that utilize high-temperature heat to produce chemical work. Like their mechanical work-producing counterparts, their efficiency depends on operating temperature and on the irreversibility of their internal processes. With this in mind, we have invented innovative design concepts for two-step solar-driven thermochemical heat engines based on iron oxide and iron oxide mixed with other metal oxides (ferrites). The design concepts utilize two sets of moving beds of ferrite reactant material in close proximity and moving in opposite directions to overcome a major impediment to achieving high efficiency--thermal recuperation between solids in efficient counter-current arrangements. They also provide inherent separation of the product hydrogen and oxygen and are an excellent match with high-concentration solar flux. However, they also impose unique requirements on the ferrite reactants and materials of construction as well as an understanding of the chemical and cycle thermodynamics. In this report the Counter-Rotating-Ring Receiver/Reactor/Recuperator (CR5) solar thermochemical heat engine and its basic operating principals are described. Preliminary thermal efficiency estimates are presented and discussed. Our ferrite reactant material development activities, thermodynamic studies, test results, and prototype hardware development are also presented.
Bad splits in bilateral sagittal split osteotomy: systematic review of fracture patterns.
Steenen, S A; Becking, A G
2016-07-01
An unfavourable and unanticipated pattern of the mandibular sagittal split osteotomy is generally referred to as a 'bad split'. Few restorative techniques to manage the situation have been described. In this article, a classification of reported bad split pattern types is proposed and appropriate salvage procedures to manage the different types of undesired fracture are presented. A systematic review was undertaken, yielding a total of 33 studies published between 1971 and 2015. These reported a total of 458 cases of bad splits among 19,527 sagittal ramus osteotomies in 10,271 patients. The total reported incidence of bad split was 2.3% of sagittal splits. The most frequently encountered were buccal plate fractures of the proximal segment (types 1A-F) and lingual fractures of the distal segment (types 2A and 2B). Coronoid fractures (type 3) and condylar neck fractures (type 4) have seldom been reported. The various types of bad split may require different salvage approaches.
Orientation modulated charge transport in hematite for photoelectrochemical water splitting
NASA Astrophysics Data System (ADS)
Cai, Jiajia; Liu, Yinglei; Li, Song; Gao, Meiqi; Wang, Dunwei; Qin, Gaowu
2016-05-01
Hematite is currently considered one of the most promising photoanode materials for light-driven water splitting. The photoelectrochemical performance of hematite is limited by its low conductivity. In this work, we demonstrate that the conductivity of hematite films can be tuned by controlling the orientation of hematite crystals. By applying a high magnetic field (up to 10 T) during the drop-casting preparation, hematite films composed of single crystal particles show featured texture by promoting those particles alignment with (001) normal to the substrate. By enhancing the photocurrent densities with tuned hematite orientation, the current method provides an effective way for increasing the number of carriers that can reach the surface.
MEASURING X-RAY VARIABILITY IN FAINT/SPARSELY SAMPLED ACTIVE GALACTIC NUCLEI
Allevato, V.; Paolillo, M.; Papadakis, I.; Pinto, C.
2013-07-01
We study the statistical properties of the normalized excess variance of variability process characterized by a ''red-noise'' power spectral density (PSD), as in the case of active galactic nuclei (AGNs). We perform Monte Carlo simulations of light curves, assuming both a continuous and a sparse sampling pattern and various signal-to-noise ratios (S/Ns). We show that the normalized excess variance is a biased estimate of the variance even in the case of continuously sampled light curves. The bias depends on the PSD slope and on the sampling pattern, but not on the S/N. We provide a simple formula to account for the bias, which yields unbiased estimates with an accuracy better than 15%. We show that the normalized excess variance estimates based on single light curves (especially for sparse sampling and S/N < 3) are highly uncertain (even if corrected for bias) and we propose instead the use of an ''ensemble estimate'', based on multiple light curves of the same object, or on the use of light curves of many objects. These estimates have symmetric distributions, known errors, and can also be corrected for biases. We use our results to estimate the ability to measure the intrinsic source variability in current data, and show that they could also be useful in the planning of the observing strategy of future surveys such as those provided by X-ray missions studying distant and/or faint AGN populations and, more in general, in the estimation of the variability amplitude of sources that will result from future surveys such as Pan-STARRS and LSST.
Measuring X-Ray Variability in Faint/Sparsely Sampled Active Galactic Nuclei
NASA Astrophysics Data System (ADS)
Allevato, V.; Paolillo, M.; Papadakis, I.; Pinto, C.
2013-07-01
We study the statistical properties of the normalized excess variance of variability process characterized by a "red-noise" power spectral density (PSD), as in the case of active galactic nuclei (AGNs). We perform Monte Carlo simulations of light curves, assuming both a continuous and a sparse sampling pattern and various signal-to-noise ratios (S/Ns). We show that the normalized excess variance is a biased estimate of the variance even in the case of continuously sampled light curves. The bias depends on the PSD slope and on the sampling pattern, but not on the S/N. We provide a simple formula to account for the bias, which yields unbiased estimates with an accuracy better than 15%. We show that the normalized excess variance estimates based on single light curves (especially for sparse sampling and S/N < 3) are highly uncertain (even if corrected for bias) and we propose instead the use of an "ensemble estimate," based on multiple light curves of the same object, or on the use of light curves of many objects. These estimates have symmetric distributions, known errors, and can also be corrected for biases. We use our results to estimate the ability to measure the intrinsic source variability in current data, and show that they could also be useful in the planning of the observing strategy of future surveys such as those provided by X-ray missions studying distant and/or faint AGN populations and, more in general, in the estimation of the variability amplitude of sources that will result from future surveys such as Pan-STARRS and LSST.
Sparse modeling of spatial environmental variables associated with asthma
Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.
2014-01-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors.
Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437
Analysis of Seismic Anisotropy Across Central Anatolia by Shear Wave Splitting
NASA Astrophysics Data System (ADS)
Pamir, Dilekcan; Abgarmi, Bizhan; Arda Özacar, A.
2014-05-01
Analysis of Seismic Anisotropy Across Central Anatolia by Shear Wave Splitting Dilekcan Pamir, Bizhan Abgarmi, A. Arda Özacar Department of Geological Engineering, Middle East Technical University (METU), Dumlupinar Bulvari 1, 06800 Ankara, Turkey Central Anatolia holds the key to connect the theories about the ongoing tectonic escape, the African Plate subduction along Cyprus Arc and the indenter-style collision of Arabian Plate along Bitlis Suture. However, the shear wave splitting measurements which are needed to characterize seismic anisotropy are very sparse in the region. Recently, seismic data recorded by national seismic networks (KOERI, ERI-DAD) with dense coverage, provided a unique opportunity to analyze the effect of present slab geometry (slab tears, slab break-off) on mantle deformation and test different models of anisotropy forming mechanisms. In this study, the anisotropic structure beneath the Central Anatolia is investigated via splitting of SKS and SKKS phases recorded at 46 broadband seismic stations. Our measurements yielded 1171 well-constrained splitting and 433 null results. Overall, the region displays NE-SW trending fast splitting directions and delay times on the order of 1 sec. On the other hand, a large number of stations which are spatially correlated with Cyprus Slab, Neogene volcanism and major tectonic structures present significant back azimuthal variations on splitting parameters that cannot be explained by one-layered anisotropy with horizontal symmetry. Thus, we have modeled anisotropy for two-layered structures using a forward approach and identified NE-SW trending fast splitting directions with delay times close to 1 sec at the lower layer and N-S, NW-SE trending fast splitting with limited time delays (0.1 - 0.3 sec) at the upper layer. Fast directions and delay times of the lower layer are similar to one-layered anisotropy and parallel or sub-parallel to the absolute plate motions which favors asthenospheric flow model
NASA Astrophysics Data System (ADS)
Deglint, Jason; Kazemzadeh, Farnoud; Wong, Alexander; Clausi, David A.
2015-09-01
One method to acquire multispectral images is to sequentially capture a series of images where each image contains information from a different bandwidth of light. Another method is to use a series of beamsplitters and dichroic filters to guide different bandwidths of light onto different cameras. However, these methods are very time consuming and expensive and perform poorly in dynamic scenes or when observing transient phenomena. An alternative strategy to capturing multispectral data is to infer this data using sparse spectral reflectance measurements captured using an imaging device with overlapping bandpass filters, such as a consumer digital camera using a Bayer filter pattern. Currently the only method of inferring dense reflectance spectra is the Wiener adaptive filter, which makes Gaussian assumptions about the data. However, these assumptions may not always hold true for all data. We propose a new technique to infer dense reflectance spectra from sparse spectral measurements through the use of a non-linear regression model. The non-linear regression model used in this technique is the random forest model, which is an ensemble of decision trees and trained via the spectral characterization of the optical imaging system and spectral data pair generation. This model is then evaluated by spectrally characterizing different patches on the Macbeth color chart, as well as by reconstructing inferred multispectral images. Results show that the proposed technique can produce inferred dense reflectance spectra that correlate well with the true dense reflectance spectra, which illustrates the merits of the technique.
Communication: Tunnelling splitting in the phosphine molecule
NASA Astrophysics Data System (ADS)
Sousa-Silva, Clara; Tennyson, Jonathan; Yurchenko, Sergey N.
2016-09-01
Splitting due to tunnelling via the potential energy barrier has played a significant role in the study of molecular spectra since the early days of spectroscopy. The observation of the ammonia doublet led to attempts to find a phosphine analogous, but these have so far failed due to its considerably higher barrier. Full dimensional, variational nuclear motion calculations are used to predict splittings as a function of excitation energy. Simulated spectra suggest that such splittings should be observable in the near infrared via overtones of the ν2 bending mode starting with 4ν2.
Budgeted phylogenetic diversity on circular split systems.
Minh, Bui Quang; Pardi, Fabio; Klaere, Steffen; von Haeseler, Arndt
2009-01-01
In the last 15 years, Phylogenetic Diversity (PD) has gained interest in the community of conservation biologists as a surrogate measure for assessing biodiversity. We have recently proposed two approaches to select taxa for maximizing PD, namely PD with budget constraints and PD on split systems. In this paper, we will unify these two strategies and present a dynamic programming algorithm to solve the unified framework of selecting taxa with maximal PD under budget constraints on circular split systems. An improved algorithm will also be given if the underlying split system is a tree.
Communication: Tunnelling splitting in the phosphine molecule.
Sousa-Silva, Clara; Tennyson, Jonathan; Yurchenko, Sergey N
2016-09-01
Splitting due to tunnelling via the potential energy barrier has played a significant role in the study of molecular spectra since the early days of spectroscopy. The observation of the ammonia doublet led to attempts to find a phosphine analogous, but these have so far failed due to its considerably higher barrier. Full dimensional, variational nuclear motion calculations are used to predict splittings as a function of excitation energy. Simulated spectra suggest that such splittings should be observable in the near infrared via overtones of the ν2 bending mode starting with 4ν2. PMID:27608982
NASA Technical Reports Server (NTRS)
2003-01-01
[figure removed for brevity, see original site]
Released 23 September 2003
A 22 km-diameter crater has been sliced by the tectonic forces that produced the rift known as Sirenum Fossae. The orientation of this rift is roughly radial to the great Tharsis volcano Arsia Mons, probably indicating a link between the formation of the rift and the volcano. Note how the rift cuts through a jumble of mounds on the floor of the crater. This indicates a sequence of events beginning with the formation of the crater followed by an infilling of material that was then eroded into the mounds and ultimately split open by the shifting martian crust.
Image information: VIS instrument. Latitude -29.7, Longitude 211.7 East (148.3 West). 19 meter/pixel resolution.
Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.
NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.
Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking
Qu, Shiru
2016-01-01
Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710
FPGA implementation of sparse matrix algorithm for information retrieval
NASA Astrophysics Data System (ADS)
Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio
2005-06-01
Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.
X-ray computed tomography using curvelet sparse regularization
Wieczorek, Matthias Vogel, Jakob; Lasser, Tobias; Frikel, Jürgen; Demaret, Laurent; Eggl, Elena; Pfeiffer, Franz; Kopp, Felix; Noël, Peter B.
2015-04-15
Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. Methods: In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Results: Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method’s strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. Conclusions: The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.
Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking
Qu, Shiru
2016-01-01
Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness.
Robust visual multitask tracking via composite sparse model
NASA Astrophysics Data System (ADS)
Jin, Bo; Jing, Zhongliang; Wang, Meng; Pan, Han
2014-11-01
Recently, multitask learning was applied to visual tracking by learning sparse particle representations in a joint task, which led to the so-called multitask tracking algorithm (MTT). Although MTT shows impressive tracking performances by mining the interdependencies between particles, the individual feature of each particle is underestimated. The utilized L1,q norm regularization assumes all features are shared between all particles and results in nearly identical representation coefficients in nonsparse rows. We propose a composite sparse multitask tracking algorithm (CSMTT). We develop a composite sparse model to formulate the object appearance as a combination of the shared feature component, the individual feature component, and the outlier component. The composite sparsity is achieved via the L and L1,1 norm minimization, and is optimized by the alternating direction method of multipliers, which provides a favorable reconstruction performance and an impressive computational efficiency. Moreover, a dynamical dictionary updating scheme is proposed to capture appearance changes. CSMTT is tested on real-world video sequences under various challenges, and experimental results show that the composite sparse model achieves noticeable lower reconstruction errors and higher computational speeds than traditional sparse models, and CSMTT has consistently better tracking performances against seven state-of-the-art trackers.
Image fusion via nonlocal sparse K-SVD dictionary learning.
Li, Ying; Li, Fangyi; Bai, Bendu; Shen, Qiang
2016-03-01
Image fusion aims to merge two or more images captured via various sensors of the same scene to construct a more informative image by integrating their details. Generally, such integration is achieved through the manipulation of the representations of the images concerned. Sparse representation plays an important role in the effective description of images, offering a great potential in a variety of image processing tasks, including image fusion. Supported by sparse representation, in this paper, an approach for image fusion by the use of a novel dictionary learning scheme is proposed. The nonlocal self-similarity property of the images is exploited, not only at the stage of learning the underlying description dictionary but during the process of image fusion. In particular, the property of nonlocal self-similarity is combined with the traditional sparse dictionary. This results in an improved learned dictionary, hereafter referred to as the nonlocal sparse K-SVD dictionary (where K-SVD stands for the K times singular value decomposition that is commonly used in the literature), and abbreviated to NL_SK_SVD. The performance of the NL_SK_SVD dictionary is applied for image fusion using simultaneous orthogonal matching pursuit. The proposed approach is evaluated with different types of images, and compared with a number of alternative image fusion techniques. The resultant superior fused images using the present approach demonstrates the efficacy of the NL_SK_SVD dictionary in sparse image representation.
Online Hierarchical Sparse Representation of Multifeature for Robust Object Tracking.
Yang, Honghong; Qu, Shiru
2016-01-01
Object tracking based on sparse representation has given promising tracking results in recent years. However, the trackers under the framework of sparse representation always overemphasize the sparse representation and ignore the correlation of visual information. In addition, the sparse coding methods only encode the local region independently and ignore the spatial neighborhood information of the image. In this paper, we propose a robust tracking algorithm. Firstly, multiple complementary features are used to describe the object appearance; the appearance model of the tracked target is modeled by instantaneous and stable appearance features simultaneously. A two-stage sparse-coded method which takes the spatial neighborhood information of the image patch and the computation burden into consideration is used to compute the reconstructed object appearance. Then, the reliability of each tracker is measured by the tracking likelihood function of transient and reconstructed appearance models. Finally, the most reliable tracker is obtained by a well established particle filter framework; the training set and the template library are incrementally updated based on the current tracking results. Experiment results on different challenging video sequences show that the proposed algorithm performs well with superior tracking accuracy and robustness. PMID:27630710
2016-01-01
Compressive Sensing (CS) theory has great potential for reconstructing Computed Tomography (CT) images from sparse-views projection data and Total Variation- (TV-) based CT reconstruction method is very popular. However, it does not directly incorporate prior images into the reconstruction. To improve the quality of reconstructed images, this paper proposed an improved TV minimization method using prior images and Split-Bregman method in CT reconstruction, which uses prior images to obtain valuable previous information and promote the subsequent imaging process. The images obtained asynchronously were registered via Locally Linear Embedding (LLE). To validate the method, two studies were performed. Numerical simulation using an abdomen phantom has been used to demonstrate that the proposed method enables accurate reconstruction of image objects under sparse projection data. A real dataset was used to further validate the method. PMID:27689076
2016-01-01
Compressive Sensing (CS) theory has great potential for reconstructing Computed Tomography (CT) images from sparse-views projection data and Total Variation- (TV-) based CT reconstruction method is very popular. However, it does not directly incorporate prior images into the reconstruction. To improve the quality of reconstructed images, this paper proposed an improved TV minimization method using prior images and Split-Bregman method in CT reconstruction, which uses prior images to obtain valuable previous information and promote the subsequent imaging process. The images obtained asynchronously were registered via Locally Linear Embedding (LLE). To validate the method, two studies were performed. Numerical simulation using an abdomen phantom has been used to demonstrate that the proposed method enables accurate reconstruction of image objects under sparse projection data. A real dataset was used to further validate the method.
Montcuquet, Anne-Sophie; Hervé, Lionel; Navarro, Fabrice; Dinten, Jean-Marc; Mars, Jérôme I
2011-09-01
Fluorescence imaging locates fluorescent markers that specifically bind to targets; like tumors, markers are injected to a patient, optimally excited with near-infrared light, and located thanks to backward-emitted fluorescence analysis. To investigate thick and diffusive media, as the fluorescence signal decreases exponentially with the light travel distance, the autofluorescence of biological tissues comes to be a limiting factor. To remove autofluorescence and isolate specific fluorescence, a spectroscopic approach, based on nonnegative matrix factorization (NMF), is explored. To improve results on spatially sparse markers detection, we suggest a new constrained NMF algorithm that takes sparsity constraints into account. A comparative study between both algorithms is proposed on simulated and in vivo data.
Chen, Lingling; Alexandrov, Yuriy; Kumar, Sunil; Andrews, Natalie; Dallman, Margaret J.; French, Paul M. W.; McGinty, James
2015-01-01
We describe an angular multiplexed imaging technique for 3-D in vivo cell tracking of sparse cell distributions and optical projection tomography (OPT) with superior time-lapse resolution and a significantly reduced light dose compared to volumetric time-lapse techniques. We demonstrate that using dual axis OPT, where two images are acquired simultaneously at different projection angles, can enable localization and tracking of features in 3-D with a time resolution equal to the camera frame rate. This is achieved with a 200x reduction in light dose compared to an equivalent volumetric time-lapse single camera OPT acquisition with 200 projection angles. We demonstrate the application of this technique to mapping the 3-D neutrophil migration pattern observed over ~25.5 minutes in a live 2 day post-fertilisation transgenic LysC:GFP zebrafish embryo following a tail wound. PMID:25909009
Divided Opinions on the Split Fovea
ERIC Educational Resources Information Center
Ellis, Andrew W.; Brysbaert, Marc
2010-01-01
We explain once again the distinction between the "split fovea theory" and the "bilateral projection theory", and consider the implications of the two theories for understanding the processing of centrally fixated words and faces.
Solar activity and oscillation frequency splittings
NASA Technical Reports Server (NTRS)
Woodard, M. F.; Libbrecht, K. G.
1993-01-01
Solar p-mode frequency splittings, parameterized by the coefficients through order N = 12 of a Legendre polynomial expansion of the mode frequencies as a function of m/L, were obtained from an analysis of helioseismology data taken at Big Bear Solar Observatory during the 4 years 1986 and 1988-1990 (approximately solar minimum to maximum). Inversion of the even-index splitting coefficients confirms that there is a significant contribution to the frequency splittings originating near the solar poles. The strength of the polar contribution is anti correlated with the overall level or solar activity in the active latitudes, suggesting a relation to polar faculae. From an analysis of the odd-index splitting coefficients we infer an uppor limit to changes in the solar equatorial near-surface rotatinal velocity of less than 1.9 m/s (3 sigma limit) between solar minimum and maximum.
Supramolecular Control over Split-Luciferase Complementation.
Bosmans, Ralph P G; Briels, Jeroen M; Milroy, Lech-Gustav; de Greef, Tom F A; Merkx, Maarten; Brunsveld, Luc
2016-07-25
Supramolecular split-enzyme complementation restores enzymatic activity and allows for on-off switching. Split-luciferase fragment pairs were provided with an N-terminal FGG sequence and screened for complementation through host-guest binding to cucurbit[8]uril (Q8). Split-luciferase heterocomplex formation was induced in a Q8 concentration dependent manner, resulting in a 20-fold upregulation of luciferase activity. Supramolecular split-luciferase complementation was fully reversible, as revealed by using two types of Q8 inhibitors. Competition studies with the weak-binding FGG peptide revealed a 300-fold enhanced stability for the formation of the ternary heterocomplex compared to binding of two of the same fragments to Q8. Stochiometric binding by the potent inhibitor memantine could be used for repeated cycling of luciferase activation and deactivation in conjunction with Q8, providing a versatile module for in vitro supramolecular signaling networks.
Sparse representation based face recognition using weighted regions
NASA Astrophysics Data System (ADS)
Bilgazyev, Emil; Yeniaras, E.; Uyanik, I.; Unan, Mahmut; Leiss, E. L.
2013-12-01
Face recognition is a challenging research topic, especially when the training (gallery) and recognition (probe) images are acquired using different cameras under varying conditions. Even a small noise or occlusion in the images can compromise the accuracy of recognition. Lately, sparse encoding based classification algorithms gave promising results for such uncontrollable scenarios. In this paper, we introduce a novel methodology by modeling the sparse encoding with weighted patches to increase the robustness of face recognition even further. In the training phase, we define a mask (i.e., weight matrix) using a sparse representation selecting the facial regions, and in the recognition phase, we perform comparison on selected facial regions. The algorithm was evaluated both quantitatively and qualitatively using two comprehensive surveillance facial image databases, i.e., SCfaceandMFPV, with the results clearly superior to common state-of-the-art methodologies in different scenarios.
Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model
NASA Astrophysics Data System (ADS)
Meng, Jia; Zhang, Jianqiu(Michelle); Qi, Yuan(Alan); Chen, Yidong; Huang, Yufei
2010-12-01
The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ([InlineEquation not available: see fulltext.]) status and Estrogen Receptor negative ([InlineEquation not available: see fulltext.]) status, respectively.
Joint sparse representation for robust multimodal biometrics recognition.
Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama
2014-01-01
Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods.
Sparse nonnegative matrix factorization with ℓ0-constraints
Peharz, Robert; Pernkopf, Franz
2012-01-01
Although nonnegative matrix factorization (NMF) favors a sparse and part-based representation of nonnegative data, there is no guarantee for this behavior. Several authors proposed NMF methods which enforce sparseness by constraining or penalizing the ℓ1-norm of the factor matrices. On the other hand, little work has been done using a more natural sparseness measure, the ℓ0-pseudo-norm. In this paper, we propose a framework for approximate NMF which constrains the ℓ0-norm of the basis matrix, or the coefficient matrix, respectively. For this purpose, techniques for unconstrained NMF can be easily incorporated, such as multiplicative update rules, or the alternating nonnegative least-squares scheme. In experiments we demonstrate the benefits of our methods, which compare to, or outperform existing approaches. PMID:22505792
Sparse representation-based image restoration via nonlocal supervised coding
NASA Astrophysics Data System (ADS)
Li, Ao; Chen, Deyun; Sun, Guanglu; Lin, Kezheng
2016-09-01
Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.
Sparse representation-based image restoration via nonlocal supervised coding
NASA Astrophysics Data System (ADS)
Li, Ao; Chen, Deyun; Sun, Guanglu; Lin, Kezheng
2016-10-01
Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.
Sparse Partial Equilibrium Tables in Chemically Resolved Reactive Flow
NASA Astrophysics Data System (ADS)
Vitello, Peter; Fried, Laurence E.; Pudliner, Brian; McAbee, Tom
2004-07-01
The detonation of an energetic material is the result of a complex interaction between kinetic chemical reactions and hydrodynamics. Unfortunately, little is known concerning the detailed chemical kinetics of detonations in energetic materials. CHEETAH uses rate laws to treat species with the slowest chemical reactions, while assuming other chemical species are in equilibrium. CHEETAH supports a wide range of elements and condensed detonation products and can also be applied to gas detonations. A sparse hash table of equation of state values is used in CHEETAH to enhance the efficiency of kinetic reaction calculations. For large-scale parallel hydrodynamic calculations, CHEETAH uses parallel communication to updates to the cache. We present here details of the sparse caching model used in the CHEETAH coupled to an ALE hydrocode. To demonstrate the efficiency of modeling using a sparse cache model we consider detonations in energetic materials.
SAR target classification based on multiscale sparse representation
NASA Astrophysics Data System (ADS)
Ruan, Huaiyu; Zhang, Rong; Li, Jingge; Zhan, Yibing
2016-03-01
We propose a novel multiscale sparse representation approach for SAR target classification. It firstly extracts the dense SIFT descriptors on multiple scales, then trains a global multiscale dictionary by sparse coding algorithm. After obtaining the sparse representation, the method applies spatial pyramid matching (SPM) and max pooling to summarize the features for each image. The proposed method can provide more information and descriptive ability than single-scale ones. Moreover, it costs less extra computation than existing multiscale methods which compute a dictionary for each scale. The MSTAR database and ship database collected from TerraSAR-X images are used in classification setup. Results show that the best overall classification rate of the proposed approach can achieve 98.83% on the MSTAR database and 92.67% on the TerraSAR-X ship database.
P-SPARSLIB: A parallel sparse iterative solution package
Saad, Y.
1994-12-31
Iterative methods are gaining popularity in engineering and sciences at a time where the computational environment is changing rapidly. P-SPARSLIB is a project to build a software library for sparse matrix computations on parallel computers. The emphasis is on iterative methods and the use of distributed sparse matrices, an extension of the domain decomposition approach to general sparse matrices. One of the goals of this project is to develop a software package geared towards specific applications. For example, the author will test the performance and usefulness of P-SPARSLIB modules on linear systems arising from CFD applications. Equally important is the goal of portability. In the long run, the author wishes to ensure that this package is portable on a variety of platforms, including SIMD environments and shared memory environments.
A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.
Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi
2015-12-01
Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.
Sparse Sensing of Aerodynamic Loads on Insect Wings
NASA Astrophysics Data System (ADS)
Manohar, Krithika; Brunton, Steven; Kutz, J. Nathan
2015-11-01
We investigate how insects use sparse sensors on their wings to detect aerodynamic loading and wing deformation using a coupled fluid-structure model given periodically flapping input motion. Recent observations suggest that insects collect sensor information about their wing deformation to inform control actions for maneuvering and rejecting gust disturbances. Given a small number of point measurements of the chordwise aerodynamic loads from the sparse sensors, we reconstruct the entire chordwise loading using sparsesensing - a signal processing technique that reconstructs a signal from a small number of measurements using l1 norm minimization of sparse modal coefficients in some basis. We compare reconstructions from sensors randomly sampled from probability distributions biased toward different regions along the wing chord. In this manner, we determine the preferred regions along the chord for sensor placement and for estimating chordwise loads to inform control decisions in flight.
Automatic landslide and mudflow detection method via multichannel sparse representation
NASA Astrophysics Data System (ADS)
Chao, Chen; Zhou, Jianjun; Hao, Zhuo; Sun, Bo; He, Jun; Ge, Fengxiang
2015-10-01
Landslide and mudflow detection is an important application of aerial images and high resolution remote sensing images, which is crucial for national security and disaster relief. Since the high resolution images are often large in size, it's necessary to develop an efficient algorithm for landslide and mudflow detection. Based on the theory of sparse representation and, we propose a novel automatic landslide and mudflow detection method in this paper, which combines multi-channel sparse representation and eight neighbor judgment methods. The whole process of the detection is totally automatic. We make the experiment on a high resolution image of ZhouQu district of Gansu province in China on August, 2010 and get a promising result which proved the effective of using sparse representation on landslide and mudflow detection.
Sparse Partial Equilibrium Tables in Chemically Resolved Reactive Flow
Vitello, P; Fried, L E; Pudliner, B; McAbee, T
2003-07-14
The detonation of an energetic material is the result of a complex interaction between kinetic chemical reactions and hydrodynamics. Unfortunately, little is known concerning the detailed chemical kinetics of detonations in energetic materials. CHEETAH uses rate laws to treat species with the slowest chemical reactions, while assuming other chemical species are in equilibrium. CHEETAH supports a wide range of elements and condensed detonation products and can also be applied to gas detonations. A sparse hash table of equation of state values, called the ''cache'' is used in CHEETAH to enhance the efficiency of kinetic reaction calculations. For large-scale parallel hydrodynamic calculations, CHEETAH uses MPI communication to updates to the cache. We present here details of the sparse caching model used in the CHEETAH. To demonstrate the efficiency of modeling using a sparse cache model we consider detonations in energetic materials.
Joint sparse representation for robust multimodal biometrics recognition.
Shekhar, Sumit; Patel, Vishal M; Nasrabadi, Nasser M; Chellappa, Rama
2014-01-01
Traditional biometric recognition systems rely on a single biometric signature for authentication. While the advantage of using multiple sources of information for establishing the identity has been widely recognized, computational models for multimodal biometrics recognition have only recently received attention. We propose a multimodal sparse representation method, which represents the test data by a sparse linear combination of training data, while constraining the observations from different modalities of the test subject to share their sparse representations. Thus, we simultaneously take into account correlations as well as coupling information among biometric modalities. A multimodal quality measure is also proposed to weigh each modality as it gets fused. Furthermore, we also kernelize the algorithm to handle nonlinearity in data. The optimization problem is solved using an efficient alternative direction method. Various experiments show that the proposed method compares favorably with competing fusion-based methods. PMID:24231870
Splitting automorphisms of free Burnside groups
Atabekyan, Varuzhan S
2013-02-28
It is proved that, if the order of a splitting automorphism of odd period n{>=}1003 of a free Burnside group B(m,n) is a prime, then the automorphism is inner. This implies, for every prime n{>=}1009, an affirmative answer to the question on the coincidence of the splitting automorphisms of period n of the group B(m,n) with the inner automorphisms (this question was posed in the 'Kourovka Notebook' in 1990). Bibliography: 17 titles.
Antenna Splitting Functions for Massive Particles
Larkoski, Andrew J.; Peskin, Michael E.; /SLAC
2011-06-22
An antenna shower is a parton shower in which the basic move is a color-coherent 2 {yields} 3 parton splitting process. In this paper, we give compact forms for the spin-dependent antenna splitting functions involving massive partons of spin 0 and spin 1/2. We hope that this formalism we have presented will be useful in describing the QCD dynamics of the top quark and other heavy particles at LHC.
Ray splitting in paraxial optical cavities.
Puentes, G; Aiello, A; Woerdman, J P
2004-03-01
We present a numerical investigation of the ray dynamics in a paraxial optical cavity when a ray-splitting mechanism is present. The cavity is a conventional two-mirror stable resonator and the ray splitting is achieved by inserting an optical beam splitter perpendicular to the cavity axis. We show that depending on the position of the beam splitter the optical resonator can become unstable and the ray dynamics displays a positive Lyapunov exponent. PMID:15089394
Spontaneous splitting of a quadruply charged vortex.
Isoshima, T; Okano, M; Yasuda, H; Kasa, K; Huhtamäki, J A M; Kumakura, M; Takahashi, Y
2007-11-16
We studied the splitting instability of a quadruply charged vortex both experimentally and theoretically. The density defect, which is a signature of the vortex core, is experimentally observed to deform into a linear shape. The deformed defect is theoretically confirmed to be an array of four linearly aligned singly charged vortices. The array of vortices rotates and precesses simultaneously with different angular velocities. The initial state of the system is not rotationally symmetric, which enables spontaneous splitting without external perturbations. PMID:18233124
Spontaneous Splitting of a Quadruply Charged Vortex
Isoshima, T.; Okano, M.; Yasuda, H.; Kasa, K.; Huhtamaeki, J. A. M.; Kumakura, M.; Takahashi, Y.
2007-11-16
We studied the splitting instability of a quadruply charged vortex both experimentally and theoretically. The density defect, which is a signature of the vortex core, is experimentally observed to deform into a linear shape. The deformed defect is theoretically confirmed to be an array of four linearly aligned singly charged vortices. The array of vortices rotates and precesses simultaneously with different angular velocities. The initial state of the system is not rotationally symmetric, which enables spontaneous splitting without external perturbations.
Content addressable systolic array for sparse matrix computation
Wing, O.
1983-01-01
A systolic array is proposed which is specifically designed to solve a system of sparse linear equations. The array consists of a number of processing elements connected in a ring. Each processing element has its own content addressable memory where the nonzero elements of the sparse matrix are stored. Matrix elements to which elementary operations are applied are extracted from the memory by content addressing. The system of equations is solved in a systolic fashion and the solution is obtained in nz+5n-2 steps where nz is the number of nonzero elements along and below the diagonal and n is the number of equations. 13 references.
Towards an Accurate Performance Modeling of Parallel SparseFactorization
Grigori, Laura; Li, Xiaoye S.
2006-05-26
We present a performance model to analyze a parallel sparseLU factorization algorithm on modern cached-based, high-end parallelarchitectures. Our model characterizes the algorithmic behavior bytakingaccount the underlying processor speed, memory system performance, aswell as the interconnect speed. The model is validated using theSuperLU_DIST linear system solver, the sparse matrices from realapplications, and an IBM POWER3 parallel machine. Our modelingmethodology can be easily adapted to study performance of other types ofsparse factorizations, such as Cholesky or QR.
D Super-Resolution Approach for Sparse Laser Scanner Data
NASA Astrophysics Data System (ADS)
Hosseinyalamdary, S.; Yilmaz, A.
2015-08-01
Laser scanner point cloud has been emerging in Photogrammetry and computer vision to achieve high level tasks such as object tracking, object recognition and scene understanding. However, low cost laser scanners are noisy, sparse and prone to systematic errors. This paper proposes a novel 3D super resolution approach to reconstruct surface of the objects in the scene. This method works on sparse, unorganized point clouds and has superior performance over other surface recovery approaches. Since the proposed approach uses anisotropic diffusion equation, it does not deteriorate the object boundaries and it preserves topology of the object.
Sparse Matrix for ECG Identification with Two-Lead Features
Tseng, Kuo-Kun; Luo, Jiao; Wang, Wenmin; Haiting, Dong
2015-01-01
Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods. PMID:25961074
A LONE code for the sparse control of quantum systems
NASA Astrophysics Data System (ADS)
Ciaramella, G.; Borzì, A.
2016-03-01
In many applications with quantum spin systems, control functions with a sparse and pulse-shaped structure are often required. These controls can be obtained by solving quantum optimal control problems with L1-penalized cost functionals. In this paper, the MATLAB package LONE is presented aimed to solving L1-penalized optimal control problems governed by unitary-operator quantum spin models. This package implements a new strategy that includes a globalized semi-smooth Krylov-Newton scheme and a continuation procedure. Results of numerical experiments demonstrate the ability of the LONE code in computing accurate sparse optimal control solutions.
BIRD: A general interface for sparse distributed memory simulators
NASA Technical Reports Server (NTRS)
Rogers, David
1990-01-01
Kanerva's sparse distributed memory (SDM) has now been implemented for at least six different computers, including SUN3 workstations, the Apple Macintosh, and the Connection Machine. A common interface for input of commands would both aid testing of programs on a broad range of computer architectures and assist users in transferring results from research environments to applications. A common interface also allows secondary programs to generate command sequences for a sparse distributed memory, which may then be executed on the appropriate hardware. The BIRD program is an attempt to create such an interface. Simplifying access to different simulators should assist developers in finding appropriate uses for SDM.
Robust head pose estimation using locality-constrained sparse coding
NASA Astrophysics Data System (ADS)
Kim, Hyunduk; Lee, Sang-Heon; Sohn, Myoung-Kyu
2015-12-01
Sparse coding (SC) method has been shown to deliver successful result in a variety of computer vision applications. However, it does not consider the underlying structure of the data in the feature space. On the other hand, locality constrained linear coding (LLC) utilizes locality constraint to project each input data into its local-coordinate system. Based on the recent success of LLC, we propose a novel locality-constrained sparse coding (LSC) method to overcome the limitation of the SC. In experiments, the proposed algorithms were applied to head pose estimation applications. Experimental results demonstrated that the LSC method is better than state-of-the-art methods.
Reconstruction Techniques for Sparse Multistatic Linear Array Microwave Imaging
Sheen, David M.; Hall, Thomas E.
2014-06-09
Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. In this paper, a sparse multi-static array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated and measured imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.
Moving target detection for frequency agility radar by sparse reconstruction
NASA Astrophysics Data System (ADS)
Quan, Yinghui; Li, YaChao; Wu, Yaojun; Ran, Lei; Xing, Mengdao; Liu, Mengqi
2016-09-01
Frequency agility radar, with randomly varied carrier frequency from pulse to pulse, exhibits superior performance compared to the conventional fixed carrier frequency pulse-Doppler radar against the electromagnetic interference. A novel moving target detection (MTD) method is proposed for the estimation of the target's velocity of frequency agility radar based on pulses within a coherent processing interval by using sparse reconstruction. Hardware implementation of orthogonal matching pursuit algorithm is executed on Xilinx Virtex-7 Field Programmable Gata Array (FPGA) to perform sparse optimization. Finally, a series of experiments are performed to evaluate the performance of proposed MTD method for frequency agility radar systems.
Qi, Jin; Yang, Zhiyong
2014-01-01
Real-time human activity recognition is essential for human-robot interactions for assisted healthy independent living. Most previous work in this area is performed on traditional two-dimensional (2D) videos and both global and local methods have been used. Since 2D videos are sensitive to changes of lighting condition, view angle, and scale, researchers begun to explore applications of 3D information in human activity understanding in recently years. Unfortunately, features that work well on 2D videos usually don't perform well on 3D videos and there is no consensus on what 3D features should be used. Here we propose a model of human activity recognition based on 3D movements of body joints. Our method has three steps, learning dictionaries of sparse codes of 3D movements of joints, sparse coding, and classification. In the first step, space-time volumes of 3D movements of body joints are obtained via dense sampling and independent component analysis is then performed to construct a dictionary of sparse codes for each activity. In the second step, the space-time volumes are projected to the dictionaries and a set of sparse histograms of the projection coefficients are constructed as feature representations of the activities. Finally, the sparse histograms are used as inputs to a support vector machine to recognize human activities. We tested this model on three databases of human activities and found that it outperforms the state-of-the-art algorithms. Thus, this model can be used for real-time human activity recognition in many applications. PMID:25473850
Iida, Y.; Yokoyama, T.; Hagenaar, H. J.
2012-06-20
Frequencies of magnetic patch processes on the supergranule boundary, namely, flux emergence, splitting, merging, and cancellation, are investigated through automatic detection. We use a set of line-of-sight magnetograms taken by the Solar Optical Telescope (SOT) on board the Hinode satellite. We found 1636 positive patches and 1637 negative patches in the data set, whose time duration is 3.5 hr and field of view is 112'' Multiplication-Sign 112''. The total numbers of magnetic processes are as follows: 493 positive and 482 negative splittings, 536 positive and 535 negative mergings, 86 cancellations, and 3 emergences. The total numbers of emergence and cancellation are significantly smaller than those of splitting and merging. Further, the frequency dependence of the merging and splitting processes on the flux content are investigated. Merging has a weak dependence on the flux content with a power-law index of only 0.28. The timescale for splitting is found to be independent of the parent flux content before splitting, which corresponds to {approx}33 minutes. It is also found that patches split into any flux contents with the same probability. This splitting has a power-law distribution of the flux content with an index of -2 as a time-independent solution. These results support that the frequency distribution of the flux content in the analyzed flux range is rapidly maintained by merging and splitting, namely, surface processes. We suggest a model for frequency distributions of cancellation and emergence based on this idea.
Quintessence and phantom emerging from the split-complex field and the split-quaternion field
NASA Astrophysics Data System (ADS)
Gao, Changjun; Chen, Xuelei; Shen, You-Gen
2016-01-01
Motivated by the mathematic theory of split-complex numbers (or hyperbolic numbers, also perplex numbers) and the split-quaternion numbers (or coquaternion numbers), we define the notion of split-complex scalar field and the split-quaternion scalar field. Then we explore the cosmic evolution of these scalar fields in the background of spatially flat Friedmann-Robertson-Walker Universe. We find that both the quintessence field and the phantom field could naturally emerge in these scalar fields. Introducing the metric of field space, these theories fall into a subclass of the multi-field theories which have been extensively studied in inflationary cosmology.
Spin splitting generated in a Y-shaped semiconductor nanostructure with a quantum point contact
Wójcik, P. Adamowski, J. Wołoszyn, M.; Spisak, B. J.
2015-07-07
We have studied the spin splitting of the current in the Y-shaped semiconductor nanostructure with a quantum point contact (QPC) in a perpendicular magnetic field. Our calculations show that the appropriate tuning of the QPC potential and the external magnetic field leads to an almost perfect separation of the spin-polarized currents: electrons with opposite spins flow out through different output branches. The spin splitting results from the joint effect of the QPC, the spin Zeeman splitting, and the electron transport through the edge states formed in the nanowire at the sufficiently high magnetic field. The Y-shaped nanostructure can be used to split the unpolarized current into two spin currents with opposite spins as well as to detect the flow of the spin current. We have found that the separation of the spin currents is only slightly affected by the Rashba spin-orbit coupling. The spin-splitter device is an analogue of the optical device—the birefractive crystal that splits the unpolarized light into two beams with perpendicular polarizations. In the magnetic-field range, in which the current is carried through the edges states, the spin splitting is robust against the spin-independent scattering. This feature opens up a possibility of the application of the Y-shaped nanostructure as a non-ballistic spin-splitter device in spintronics.
Spin splitting generated in a Y-shaped semiconductor nanostructure with a quantum point contact
NASA Astrophysics Data System (ADS)
Wójcik, P.; Adamowski, J.; Wołoszyn, M.; Spisak, B. J.
2015-07-01
We have studied the spin splitting of the current in the Y-shaped semiconductor nanostructure with a quantum point contact (QPC) in a perpendicular magnetic field. Our calculations show that the appropriate tuning of the QPC potential and the external magnetic field leads to an almost perfect separation of the spin-polarized currents: electrons with opposite spins flow out through different output branches. The spin splitting results from the joint effect of the QPC, the spin Zeeman splitting, and the electron transport through the edge states formed in the nanowire at the sufficiently high magnetic field. The Y-shaped nanostructure can be used to split the unpolarized current into two spin currents with opposite spins as well as to detect the flow of the spin current. We have found that the separation of the spin currents is only slightly affected by the Rashba spin-orbit coupling. The spin-splitter device is an analogue of the optical device—the birefractive crystal that splits the unpolarized light into two beams with perpendicular polarizations. In the magnetic-field range, in which the current is carried through the edges states, the spin splitting is robust against the spin-independent scattering. This feature opens up a possibility of the application of the Y-shaped nanostructure as a non-ballistic spin-splitter device in spintronics.
Genetically-Directed, Cell Type-Specific Sparse Labeling for the Analysis of Neuronal Morphology
Rotolo, Thomas; Smallwood, Philip M.; Williams, John; Nathans, Jeremy
2008-01-01
Background In mammals, genetically-directed cell labeling technologies have not yet been applied to the morphologic analysis of neurons with very large and complex arbors, an application that requires extremely sparse labeling and that is only rendered practical by limiting the labeled population to one or a few predetermined neuronal subtypes. Methods and Findings In the present study we have addressed this application by using CreER technology to non-invasively label very small numbers of neurons so that their morphologies can be fully visualized. Four lines of IRES-CreER knock-in mice were constructed to permit labeling selectively in cholinergic or catecholaminergic neurons [choline acetyltransferase (ChAT)-IRES-CreER or tyrosine hydroxylase (TH)-IRES-CreER], predominantly in projection neurons [neurofilament light chain (NFL)-IRES-CreER], or broadly in neurons and some glia [vesicle-associated membrane protein2 (VAMP2)-IRES-CreER]. When crossed to the Z/AP reporter and exposed to 4-hydroxytamoxifen in the early postnatal period, the number of neurons expressing the human placental alkaline phosphatase reporter can be reproducibly lowered to fewer than 50 per brain. Sparse Cre-mediated recombination in ChAT-IRES-CreER;Z/AP mice shows the full axonal and dendritic arbors of individual forebrain cholinergic neurons, the first time that the complete morphologies of these very large neurons have been revealed in any species. Conclusions Sparse genetically-directed, cell type-specific neuronal labeling with IRES-creER lines should prove useful for studying a wide variety of questions in neuronal development and disease. PMID:19116659
Two demonstrators and a simulator for a sparse, distributed memory
NASA Technical Reports Server (NTRS)
Brown, Robert L.
1987-01-01
Described are two programs demonstrating different aspects of Kanerva's Sparse, Distributed Memory (SDM). These programs run on Sun 3 workstations, one using color, and have straightforward graphically oriented user interfaces and graphical output. Presented are descriptions of the programs, how to use them, and what they show. Additionally, this paper describes the software simulator behind each program.
Remote sensing image fusion via wavelet transform and sparse representation
NASA Astrophysics Data System (ADS)
Cheng, Jian; Liu, Haijun; Liu, Ting; Wang, Feng; Li, Hongsheng
2015-06-01
In this paper, we propose a remote sensing image fusion method which combines the wavelet transform and sparse representation to obtain fusion images with high spectral resolution and high spatial resolution. Firstly, intensity-hue-saturation (IHS) transform is applied to Multi-Spectral (MS) images. Then, wavelet transform is used to the intensity component of MS images and the Panchromatic (Pan) image to construct the multi-scale representation respectively. With the multi-scale representation, different fusion strategies are taken on the low-frequency and the high-frequency sub-images. Sparse representation with training dictionary is introduced into the low-frequency sub-image fusion. The fusion rule for the sparse representation coefficients of the low-frequency sub-images is defined by the spatial frequency maximum. For high-frequency sub-images with prolific detail information, the fusion rule is established by the images information fusion measurement indicator. Finally, the fused results are obtained through inverse wavelet transform and inverse IHS transform. The wavelet transform has the ability to extract the spectral information and the global spatial details from the original pairwise images, while sparse representation can extract the local structures of images effectively. Therefore, our proposed fusion method can well preserve the spectral information and the spatial detail information of the original images. The experimental results on the remote sensing images have demonstrated that our proposed method could well maintain the spectral characteristics of fusion images with a high spatial resolution.
Estimating Population Characteristics from Sparse Matrix Samples of Item Responses.
ERIC Educational Resources Information Center
Mislevy, Robert J.; And Others
1992-01-01
Concepts behind plausible values in estimating population characteristics from sparse matrix samples of item responses are discussed. The use of marginal analyses is described in the context of the National Assessment of Educational Progress, and the approach is illustrated with Scholastic Aptitude Test data for 9,075 high school seniors. (SLD)
Robust Methods for Sensing and Reconstructing Sparse Signals
ERIC Educational Resources Information Center
Carrillo, Rafael E.
2012-01-01
Compressed sensing (CS) is an emerging signal acquisition framework that goes against the traditional Nyquist sampling paradigm. CS demonstrates that a sparse, or compressible, signal can be acquired using a low rate acquisition process. Since noise is always present in practical data acquisition systems, sensing and reconstruction methods are…
Image Super-Resolution via Adaptive Regularization and Sparse Representation.
Cao, Feilong; Cai, Miaomiao; Tan, Yuanpeng; Zhao, Jianwei
2016-07-01
Previous studies have shown that image patches can be well represented as a sparse linear combination of elements from an appropriately selected over-complete dictionary. Recently, single-image super-resolution (SISR) via sparse representation using blurred and downsampled low-resolution images has attracted increasing interest, where the aim is to obtain the coefficients for sparse representation by solving an l0 or l1 norm optimization problem. The l0 optimization is a nonconvex and NP-hard problem, while the l1 optimization usually requires many more measurements and presents new challenges even when the image is the usual size, so we propose a new approach for SISR recovery based on regularization nonconvex optimization. The proposed approach is potentially a powerful method for recovering SISR via sparse representations, and it can yield a sparser solution than the l1 regularization method. We also consider the best choice for lp regularization with all p in (0, 1), where we propose a scheme that adaptively selects the norm value for each image patch. In addition, we provide a method for estimating the best value of the regularization parameter λ adaptively, and we discuss an alternate iteration method for selecting p and λ . We perform experiments, which demonstrates that the proposed regularization nonconvex optimization method can outperform the convex optimization method and generate higher quality images.
Beam hardening correction for sparse-view CT reconstruction
NASA Astrophysics Data System (ADS)
Liu, Wenlei; Rong, Junyan; Gao, Peng; Liao, Qimei; Lu, HongBing
2015-03-01
Beam hardening, which is caused by spectrum polychromatism of the X-ray beam, may result in various artifacts in the reconstructed image and degrade image quality. The artifacts would be further aggravated for the sparse-view reconstruction due to insufficient sampling data. Considering the advantages of the total-variation (TV) minimization in CT reconstruction with sparse-view data, in this paper, we propose a beam hardening correction method for sparse-view CT reconstruction based on Brabant's modeling. In this correction model for beam hardening, the attenuation coefficient of each voxel at the effective energy is modeled and estimated linearly, and can be applied in an iterative framework, such as simultaneous algebraic reconstruction technique (SART). By integrating the correction model into the forward projector of the algebraic reconstruction technique (ART), the TV minimization can recover images when only a limited number of projections are available. The proposed method does not need prior information about the beam spectrum. Preliminary validation using Monte Carlo simulations indicates that the proposed method can provide better reconstructed images from sparse-view projection data, with effective suppression of artifacts caused by beam hardening. With appropriate modeling of other degrading effects such as photon scattering, the proposed framework may provide a new way for low-dose CT imaging.
Hyperspherical Sparse Approximation Techniques for High-Dimensional Discontinuity Detection
Zhang, Guannan; Webster, Clayton G.; Gunzburger, Max; Burkardt, John
2016-08-04
This work proposes a hyperspherical sparse approximation framework for detecting jump discontinuities in functions in high-dimensional spaces. The need for a novel approach results from the theoretical and computational inefficiencies of well-known approaches, such as adaptive sparse grids, for discontinuity detection. Our approach constructs the hyperspherical coordinate representation of the discontinuity surface of a function. Then sparse approximations of the transformed function are built in the hyperspherical coordinate system, with values at each point estimated by solving a one-dimensional discontinuity detection problem. Due to the smoothness of the hypersurface, the new technique can identify jump discontinuities with significantly reduced computationalmore » cost, compared to existing methods. Several approaches are used to approximate the transformed discontinuity surface in the hyperspherical system, including adaptive sparse grid and radial basis function interpolation, discrete least squares projection, and compressed sensing approximation. Moreover, hierarchical acceleration techniques are also incorporated to further reduce the overall complexity. In conclusion, rigorous complexity analyses of the new methods are provided, as are several numerical examples that illustrate the effectiveness of our approach.« less
HYPOTHESIS TESTING FOR HIGH-DIMENSIONAL SPARSE BINARY REGRESSION
Mukherjee, Rajarshi; Pillai, Natesh S.; Lin, Xihong
2015-01-01
In this paper, we study the detection boundary for minimax hypothesis testing in the context of high-dimensional, sparse binary regression models. Motivated by genetic sequencing association studies for rare variant effects, we investigate the complexity of the hypothesis testing problem when the design matrix is sparse. We observe a new phenomenon in the behavior of detection boundary which does not occur in the case of Gaussian linear regression. We derive the detection boundary as a function of two components: a design matrix sparsity index and signal strength, each of which is a function of the sparsity of the alternative. For any alternative, if the design matrix sparsity index is too high, any test is asymptotically powerless irrespective of the magnitude of signal strength. For binary design matrices with the sparsity index that is not too high, our results are parallel to those in the Gaussian case. In this context, we derive detection boundaries for both dense and sparse regimes. For the dense regime, we show that the generalized likelihood ratio is rate optimal; for the sparse regime, we propose an extended Higher Criticism Test and show it is rate optimal and sharp. We illustrate the finite sample properties of the theoretical results using simulation studies. PMID:26246645
Sparse principal component analysis in medical shape modeling
NASA Astrophysics Data System (ADS)
Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus
2006-03-01
Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.
Sparse code of conflict in a primate society
Daniels, Bryan C.; Krakauer, David C.; Flack, Jessica C.
2012-01-01
Animals living in groups collectively produce social structure. In this context individuals make strategic decisions about when to cooperate and compete. This requires that individuals can perceive patterns in collective dynamics, but how this pattern extraction occurs is unclear. Our goal is to identify a model that extracts meaningful social patterns from a behavioral time series while remaining cognitively parsimonious by making the fewest demands on memory. Using fine-grained conflict data from macaques, we show that sparse coding, an important principle of neural compression, is an effective method for compressing collective behavior. The sparse code is shown to be efficient, predictive, and socially meaningful. In our monkey society, the sparse code of conflict is composed of related individuals, the policers, and the alpha female. Our results suggest that sparse coding is a natural technique for pattern extraction when cognitive constraints and small sample sizes limit the complexity of inferential models. Our approach highlights the need for cognitive experiments addressing how individuals perceive collective features of social organization. PMID:22891296
A multithread based new sparse matrix method in bioluminescence tomography
NASA Astrophysics Data System (ADS)
Zhang, Bo; Tian, Jie; Liu, Dan; Sun, Li; Yang, Xin; Han, Dong
2010-03-01
Among many molecular imaging modalities, bioluminescence tomography (BLT) stands out as an effective approach for in vivo imaging because of its noninvasive molecular and cellular level detection ability, high sensitivity and low cost in comparison with other imaging technologies. However, there exists the case that large scale problem with large number of points and elements in the structure of mesh standing for the small animal or phantom. And the large scale problem's system matrix generated by the diffuse approximation (DA) model using finite element method (FEM) is large. So there wouldn't be enough random access memory (RAM) for the program and the related inverse problem couldn't be solved. Considering the sparse property of the BLT system matrix, we've developed a new sparse matrix (ZSM) to overcome the problem. And the related algorithms have all been speeded up by multi-thread technologies. Then the inverse problem is solved by Tikhonov regularization method in adaptive finite element (AFE) framework. Finally, the performance of this method is tested on a heterogeneous phantom and the boundary data is obtained through Monte Carlo simulation. During the process of solving the forward model, the ZSM can save more processing time and memory space than the usual way, such as those not using sparse matrix and those using Triples or Cross Linked sparse matrix. Numerical experiments have shown when more CPU cores are used, the processing speed is increased. By incorporating ZSM, BLT can be applied to large scale problems with large system matrix.
Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.
Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi
2016-01-01
The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.
Discriminative object tracking via sparse representation and online dictionary learning.
Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua
2014-04-01
We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.
Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules
Sacramento, João; Wichert, Andreas; van Rossum, Mark C. W.
2015-01-01
It is believed that energy efficiency is an important constraint in brain evolution. As synaptic transmission dominates energy consumption, energy can be saved by ensuring that only a few synapses are active. It is therefore likely that the formation of sparse codes and sparse connectivity are fundamental objectives of synaptic plasticity. In this work we study how sparse connectivity can result from a synaptic learning rule of excitatory synapses. Information is maximised when potentiation and depression are balanced according to the mean presynaptic activity level and the resulting fraction of zero-weight synapses is around 50%. However, an imbalance towards depression increases the fraction of zero-weight synapses without significantly affecting performance. We show that imbalanced plasticity corresponds to imposing a regularising constraint on the L 1-norm of the synaptic weight vector, a procedure that is well-known to induce sparseness. Imbalanced plasticity is biophysically plausible and leads to more efficient synaptic configurations than a previously suggested approach that prunes synapses after learning. Our framework gives a novel interpretation to the high fraction of silent synapses found in brain regions like the cerebellum. PMID:26046817
Half-quadratic-based iterative minimization for robust sparse representation.
He, Ran; Zheng, Wei-Shi; Tan, Tieniu; Sun, Zhenan
2014-02-01
Robust sparse representation has shown significant potential in solving challenging problems in computer vision such as biometrics and visual surveillance. Although several robust sparse models have been proposed and promising results have been obtained, they are either for error correction or for error detection, and learning a general framework that systematically unifies these two aspects and explores their relation is still an open problem. In this paper, we develop a half-quadratic (HQ) framework to solve the robust sparse representation problem. By defining different kinds of half-quadratic functions, the proposed HQ framework is applicable to performing both error correction and error detection. More specifically, by using the additive form of HQ, we propose an ℓ1-regularized error correction method by iteratively recovering corrupted data from errors incurred by noises and outliers; by using the multiplicative form of HQ, we propose an ℓ1-regularized error detection method by learning from uncorrupted data iteratively. We also show that the ℓ1-regularization solved by soft-thresholding function has a dual relationship to Huber M-estimator, which theoretically guarantees the performance of robust sparse representation in terms of M-estimation. Experiments on robust face recognition under severe occlusion and corruption validate our framework and findings.
Gene network-based cancer prognosis analysis with sparse boosting
Ma, Shuangge; Huang, Yuan; Huang, Jian; Fang, Kuangnan
2013-01-01
Summary High-throughput gene profiling studies have been extensively conducted, searching for markers associated with cancer development and progression. In this study, we analyse cancer prognosis studies with right censored survival responses. With gene expression data, we adopt the weighted gene co-expression network analysis (WGCNA) to describe the interplay among genes. In network analysis, nodes represent genes. There are subsets of nodes, called modules, which are tightly connected to each other. Genes within the same modules tend to have co-regulated biological functions. For cancer prognosis data with gene expression measurements, our goal is to identify cancer markers, while properly accounting for the network module structure. A two-step sparse boosting approach, called Network Sparse Boosting (NSBoost), is proposed for marker selection. In the first step, for each module separately, we use a sparse boosting approach for within-module marker selection and construct module-level ‘super markers ’. In the second step, we use the super markers to represent the effects of all genes within the same modules and conduct module-level selection using a sparse boosting approach. Simulation study shows that NSBoost can more accurately identify cancer-associated genes and modules than alternatives. In the analysis of breast cancer and lymphoma prognosis studies, NSBoost identifies genes with important biological implications. It outperforms alternatives including the boosting and penalization approaches by identifying a smaller number of genes/modules and/or having better prediction performance. PMID:22950901
STIS Sparse Field CTE test-internal {Cycle 10}
NASA Astrophysics Data System (ADS)
Goudfrooij, Paul
2001-07-01
CTE measurements are made using the "sparse field test", along both the serial and parallel axes. This program needs special commanding to provide {a} off-center MSM positionings of some slits, and {b} the ability to read out with any amplifier {A, B, C, or D}. All exposures are internals.
Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering
Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi
2016-01-01
The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children. PMID:27199650
Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering
Sicat, Ronell; Krüger, Jens; Möller, Torsten; Hadwiger, Markus
2015-01-01
This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs. PMID:26146475
Efficient Coordinated Recovery of Sparse Channels in Massive MIMO
NASA Astrophysics Data System (ADS)
Masood, Mudassir; Afify, Laila H.; Al-Naffouri, Tareq Y.
2015-01-01
This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and require a small number of pilots. Two algorithms based on this approach have been developed which perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.
An adaptive hierarchical sensing scheme for sparse signals
NASA Astrophysics Data System (ADS)
Schütze, Henry; Barth, Erhardt; Martinetz, Thomas
2014-02-01
In this paper, we present Adaptive Hierarchical Sensing (AHS), a novel adaptive hierarchical sensing algorithm for sparse signals. For a given but unknown signal with a sparse representation in an orthogonal basis, the sensing task is to identify its non-zero transform coefficients by performing only few measurements. A measurement is simply the inner product of the signal and a particular measurement vector. During sensing, AHS partially traverses a binary tree and performs one measurement per visited node. AHS is adaptive in the sense that after each measurement a decision is made whether the entire subtree of the current node is either further traversed or omitted depending on the measurement value. In order to acquire an N -dimensional signal that is K-sparse, AHS performs O(K log N/K) measurements. With AHS, the signal is easily reconstructed by a basis transform without the need to solve an optimization problem. When sensing full-size images, AHS can compete with a state-of-the-art compressed sensing approach in terms of reconstruction performance versus number of measurements. Additionally, we simulate the sensing of image patches by AHS and investigate the impact of the choice of the sparse coding basis as well as the impact of the tree composition.
10 CFR 26.113 - Splitting the urine specimen.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 10 Energy 1 2013-01-01 2013-01-01 false Splitting the urine specimen. 26.113 Section 26.113 Energy... Splitting the urine specimen. (a) Licensees and other entities may, but are not required to, use split-specimen methods of collection. (b) If the urine specimen is to be split into two specimen...
10 CFR 26.113 - Splitting the urine specimen.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 10 Energy 1 2012-01-01 2012-01-01 false Splitting the urine specimen. 26.113 Section 26.113 Energy... Splitting the urine specimen. (a) Licensees and other entities may, but are not required to, use split-specimen methods of collection. (b) If the urine specimen is to be split into two specimen...
10 CFR 26.113 - Splitting the urine specimen.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 10 Energy 1 2014-01-01 2014-01-01 false Splitting the urine specimen. 26.113 Section 26.113 Energy... Splitting the urine specimen. (a) Licensees and other entities may, but are not required to, use split-specimen methods of collection. (b) If the urine specimen is to be split into two specimen...
NASA Astrophysics Data System (ADS)
Hashemi, Nezhad Z.; Karami, A.
2015-10-01
Hyperspectral images (HSI) have high spectral and low spatial resolutions. However, multispectral images (MSI) usually have low spectral and high spatial resolutions. In various applications HSI with high spectral and spatial resolutions are required. In this paper, a new method for spatial resolution enhancement of HSI using high resolution MSI based on sparse coding and linear spectral unmixing (SCLSU) is introduced. In the proposed method (SCLSU), high spectral resolution features of HSI and high spatial resolution features of MSI are fused. In this case, the sparse representation of some high resolution MSI and linear spectral unmixing (LSU) model of HSI and MSI is simultaneously used in order to construct high resolution HSI (HRHSI). The fusion process of HSI and MSI is formulated as an ill-posed inverse problem. It is solved by the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) and an orthogonal matching pursuit (OMP) algorithm. Finally, the proposed algorithm is applied to the Hyperion and ALI datasets. Compared with the other state-of-the-art algorithms such as Coupled Nonnegative Matrix Factorization (CNMF) and local spectral unmixing, the SCLSU has significantly increased the spatial resolution and in addition the spectral content of HSI is well maintained.