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.
Local Sparse Structure Denoising for Low-Light-Level Image.
Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa
2015-12-01
Sparse and redundant representations perform well in image denoising. However, sparsity-based methods fail to denoise low-light-level (LLL) images because of heavy and complex noise. They consider sparsity on image patches independently and tend to lose the texture structures. To suppress noises and maintain textures simultaneously, it is necessary to embed noise invariant features into the sparse decomposition process. We, therefore, used a local structure preserving sparse coding (LSPSc) formulation to explore the local sparse structures (both the sparsity and local structure) in image. It was found that, with the introduction of spatial local structure constraint into the general sparse coding algorithm, LSPSc could improve the robustness of sparse representation for patches in serious noise. We further used a kernel LSPSc (K-LSPSc) formulation, which extends LSPSc into the kernel space to weaken the influence of linear structure constraint in nonlinear data. Based on the robust LSPSc and K-LSPSc algorithms, we constructed a local sparse structure denoising (LSSD) model for LLL images, which was demonstrated to give high performance in the natural LLL images denoising, indicating that both the LSPSc- and K-LSPSc-based LSSD models have the stable property of noise inhibition and texture details preservation.
Muon loop light-by-light contribution to hyperfine splitting in muonium.
Eides, Michael I; Shelyuto, Valery A
2014-05-02
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.
Study on a splitting-light optical system for spectrometer
NASA Astrophysics Data System (ADS)
Ren, Zhong; Liu, Guodong; Huang, Zhen; Xiong, Zhihua
2015-07-01
With the development of holography technique and nano-superfinishing technique, holography grating has being used into the spectrometer. To overcome some drawbacks of optical system for traditional plane and concave grating typed spectrometer, a splitting-light optical system for spectrometer based on volume phase holographic transmission (VPHT) grating is designed and developed in this paper. Meanwhile, the principle of VPHT grating is introduced by using the coupled-wave theory, and the relationship between the diffraction efficiency of the VPHT and the grating depth and the irradiation wavelength are simulated by means of MATLAB numerical computing method. In order to validate this splitting-light optical system, the experiment of measuring spectral resolution is performed and the spectral resolution reached 2nm, a calibration equation between the diffraction wavelengths and the shift of the corresponding wavelengths is obtained by using polynomial fitting algorithm. The experimental results demonstrate that the design of the splitting-light optical system for spectrometer based on VPHT grating is feasible.
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
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.
Point-source reconstruction with a sparse light-sensor array for optical TPC readout
NASA Astrophysics Data System (ADS)
Rutter, G.; Richards, M.; Bennieston, A. J.; Ramachers, Y. A.
2011-07-01
A reconstruction technique for sparse array optical signal readout is introduced and applied to the generic challenge of large-area readout of a large number of point light sources. This challenge finds a prominent example in future, large volume neutrino detector studies based on liquid argon. It is concluded that the sparse array option may be ruled out for reasons of required number of channels when compared to a benchmark derived from charge readout on wire-planes. Smaller-scale detectors, however, could benefit from this technology.
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.
Surface nanostructures in photocatalysts for visible-light-driven water splitting.
Maeda, Kazuhiko; Domen, Kazunari
2011-01-01
Overall water splitting to form hydrogen and oxygen over a heterogeneous (particulate) photocatalyst with solar energy is a promising process for clean and recyclable hydrogen production on a large-scale. In recent years, numerous attempts have been made for the development of photocatalysts that work under visible-light to utilize solar energy efficiently. This chapter describes recent research progress on heterogeneous photocatalysis for water splitting with visible light, particularly focusing on the development of nanostructured cocatalysts made by the authors' group.
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.
Graphene-based materials for hydrogen generation from light-driven water splitting.
Xie, Guancai; Zhang, Kai; Guo, Beidou; Liu, Qian; Fang, Liang; Gong, Jian Ru
2013-07-26
Hydrogen production from solar water splitting has been considered as an ultimate solution to the energy and environmental issues. Over the past few years, graphene has made great contribution to improving the light-driven hydrogen generation performance. This article provides a comprehensive overview of the recent research progress on graphene-based materials for hydrogen evolution from light-driven water splitting. It begins with a brief introduction of the current status and basic principles of hydrogen generation from solar water splitting, and tailoring properties of graphene for application in this area. Then, the roles of graphene in hydrogen generation reaction, including an electron acceptor and transporter, a cocatalyst, a photocatalyst, and a photosensitizer, are elaborated respectively. After that, the comparison between graphene and other carbon materials in solar water splitting is made. Last, this review is concluded with remarks on some challenges and perspectives in this emerging field.
Recent progress in oxynitride photocatalysts for visible-light-driven water splitting
Takata, Tsuyoshi; Pan, Chengsi; Domen, Kazunari
2015-01-01
Photocatalytic water splitting into hydrogen and oxygen is a method to directly convert light energy into storable chemical energy, and has received considerable attention for use in large-scale solar energy utilization. Particulate semiconductors are generally used as photocatalysts, and semiconductor properties such as bandgap, band positions, and photocarrier mobility can heavily impact photocatalytic performance. The design of active photocatalysts has been performed with the consideration of such semiconductor properties. Photocatalysts have a catalytic aspect in addition to a semiconductor one. The ability to control surface redox reactions in order to efficiently produce targeted reactants is also important for photocatalysts. Over the past few decades, various photocatalysts for water splitting have been developed, and a recent main concern has been the development of visible-light sensitive photocatalysts for water splitting. This review introduces the study of water-splitting photocatalysts, with a focus on recent progress in visible-light induced overall water splitting on oxynitride photocatalysts. Various strategies for designing efficient photocatalysts for water splitting are also discussed herein. PMID:27877787
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, 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.
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.
Effect of hyperfine splitting on light-induced drift
NASA Astrophysics Data System (ADS)
Parkhomenko, A. I.; Shalagin, A. M.
1986-09-01
The influence of the hyperfine structure (hfs) of the levels upon the light-induced drift (LID) effect is investigated. It is shown that hfs considerably affects the dependence of the LID velocity upon the radiation frequency. It is concluded that for decreasing separation between the hfs components the LID effect can both increase and decrease depending upon the relationship of the system parameters (collision frequencies in different levels, the pressure of a buffer gas, etc.). A considerable decrease of the effect however is highly unlikely. It is shown that a change in the buffer gas pressure can lead to reversal of the LID velocity direction.
Period Estimation for Sparsely-sampled Quasi-periodic Light Curves Applied to Miras
NASA Astrophysics Data System (ADS)
He, Shiyuan; Yuan, Wenlong; Huang, Jianhua Z.; Long, James; Macri, Lucas M.
2016-12-01
We develop a nonlinear semi-parametric Gaussian process model to estimate periods of Miras with sparsely sampled light curves. The model uses a sinusoidal basis for the periodic variation and a Gaussian process for the stochastic changes. We use maximum likelihood to estimate the period and the parameters of the Gaussian process, while integrating out the effects of other nuisance parameters in the model with respect to a suitable prior distribution obtained from earlier studies. Since the likelihood is highly multimodal for period, we implement a hybrid method that applies the quasi-Newton algorithm for Gaussian process parameters and search the period/frequency parameter space over a dense grid. A large-scale, high-fidelity simulation is conducted to mimic the sampling quality of Mira light curves obtained by the M33 Synoptic Stellar Survey. The simulated data set is publicly available and can serve as a testbed for future evaluation of different period estimation methods. The semi-parametric model outperforms an existing algorithm on this simulated test data set as measured by period recovery rate and quality of the resulting period-luminosity relations.
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
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.
Polaritonic normal-mode splitting and light localization in a one-dimensional nanoguide
NASA Astrophysics Data System (ADS)
Haakh, Harald R.; Faez, Sanli; Sandoghdar, Vahid
2016-11-01
We theoretically investigate the interaction of light and a collection of emitters in a subwavelength one-dimensional medium (nanoguide), where enhanced emitter-photon coupling leads to efficient multiple scattering of photons. We show that the spectrum of the transmitted light undergoes normal-mode splitting even though no external cavity resonance is employed. By considering densities much higher than those encountered in cold atom experiments, we study the influence of the near-field dipole coupling and disorder on the resulting complex super-radiant and subradiant polaritonic states. In particular, we provide evidence for the longitudinal localization of light in a one-dimensional open system and provide a polaritonic phase diagram. Our results motivate a number of experiments, where new coherent superposition states of light and matter can be realized in the solid state.
Hetero-type dual photoanodes for unbiased solar water splitting with extended light harvesting.
Kim, Jin Hyun; Jang, Ji-Wook; Jo, Yim Hyun; Abdi, Fatwa F; Lee, Young Hye; van de Krol, Roel; Lee, Jae Sung
2016-12-14
Metal oxide semiconductors are promising photoelectrode materials for solar water splitting due to their robustness in aqueous solutions and low cost. Yet, their solar-to-hydrogen conversion efficiencies are still not high enough for practical applications. Here we present a strategy to enhance the efficiency of metal oxides, hetero-type dual photoelectrodes, in which two photoanodes of different bandgaps are connected in parallel for extended light harvesting. Thus, a photoelectrochemical device made of modified BiVO4 and α-Fe2O3 as dual photoanodes utilizes visible light up to 610 nm for water splitting, and shows stable photocurrents of 7.0±0.2 mA cm(-2) at 1.23 VRHE under 1 sun irradiation. A tandem cell composed with the dual photoanodes-silicon solar cell demonstrates unbiased water splitting efficiency of 7.7%. These results and concept represent a significant step forward en route to the goal of >10% efficiency required for practical solar hydrogen production.
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
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.
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.
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.
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)
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.
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
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.
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.
Chiral molecules split light: Reflection and refraction in a chiral liquid.
Ghosh, Ambarish; Fischer, Peer
2006-10-27
A light beam changes direction as it enters a liquid at an angle from another medium, such as air. Should the liquid contain molecules that lack mirror symmetry, then it has been predicted by Fresnel that the light beam will not only change direction, but will actually split into two separate beams with a small difference in the respective angles of refraction. Here we report the observation of this phenomenon. We also demonstrate that the angle of reflection does not equal the angle of incidence in a chiral medium. Unlike conventional optical rotation, which depends on the path-length through the sample, the reported reflection and refraction phenomena arise within a few wavelengths at the interface and thereby suggest a new approach to polarimetry that can be used in microfluidic volumes.
Reaction pattern and mechanism of light induced oxidative water splitting in photosynthesis.
Renger, Gernot; Kühn, Philipp
2007-06-01
This mini review is an attempt to briefly summarize our current knowledge on light driven oxidative water splitting in photosynthesis. The reaction leading to molecular oxygen and four protons via photosynthesis comprises thermodynamic and kinetic constraints that require a balanced fine tuning of the reaction coordinates. The mode of coupling between electron (ET) and proton transfer (PT) reactions is shown to be of key mechanistic relevance for the redox turnover of Y(Z) and the reactions within the WOC. The WOC is characterized by peculiar energetics of its oxidation steps in the WOC. In all oxygen evolving photosynthetic organisms the redox state S(1) is thermodynamically most stable and therefore this general feature is assumed to be of physiological relevance. Available information on the Gibbs energy differences between the individual redox states S(i+1) and S(i) and on the activation energies of their oxidative transitions are used to construct a general reaction coordinate of oxidative water splitting in photosystem II (PS II). Finally, an attempt is presented to cast our current state of knowledge into a mechanism of oxidative water splitting with special emphasis on the formation of the essential O-O bond and the active role of the protein environment in tuning the local proton activity that depends on time and redox state S(i). The O-O linkage is assumed to take place within a multistate equilibrium at the redox level of S(3), comprising both redox isomerism and proton tautomerism. It is proposed that one state, S(3)(P), attains an electronic configuration and nuclear geometry that corresponds with a hydrogen bonded peroxide which acts as the entatic state for the generation of complexed molecular oxygen through S(3)(P) oxidation by Y(Z)(ox).
Hirmer, M; Hirmer, M; Schuh, D; Wegscheider, W; Korn, T; Winkler, R; Schüller, C
2011-11-18
In resonant inelastic light scattering experiments on two-dimensional hole systems in GaAs-Al(x)Ga(1-x)As single quantum wells we find evidence for the strongly anisotropic spin-split hole dispersion at finite in-plane momenta. In all our samples we detect a low-energy spin-density excitation of a few meV, stemming from excitation of holes of the spin-split ground state. The detailed spectral shape of the excitation depends sensitively on the orientations of the linear light polarizations with respect to the in-plane crystal axes. In particular, we observe a doublet structure, which is most pronounced if the polarization of the incident light is parallel to the [110] in-plane direction. Theoretical calculations of the Raman spectra based on a multiband k · p approach confirm that the observed doublet structure is due to the anisotropic spin-split hole dispersion.
Fujito, Hironori; Kunioku, Hironobu; Kato, Daichi; Suzuki, Hajime; Higashi, Masanobu; Kageyama, Hiroshi; Abe, Ryu
2016-02-24
Mixed anion compounds are expected to be a photocatalyst for visible light-induced water splitting, but the available materials have been almost limited to oxynitrides. Here, we show that an oxychrolide Bi4NbO8Cl, a single layer Sillen-Aurivillius perovskite, is a stable and efficient O2-evolving photocatalyst under visible light, enabling a Z-scheme overall water splitting by coupling with a H2-evolving photocatalyst (Rh-doped SrTiO3). It is found that the valence band maximum of Bi4NbO8Cl is unusually high owing to highly dispersive O-2p orbitals (not Cl-3p orbitals), affording the narrow band gap and possibly the stability against water oxidation. This study suggests that a family of Sillen-Aurivillius perovskite oxyhalides is a promising system to allow a versatile band level tuning for establishing efficient and stable water-splitting under visible light.
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.
Liu, Jiang-Tao; Deng, Xin-Hua; Yang, Wen; Li, Jun
2015-02-07
The optical absorption of nanoscale thickness semiconductor films on top of light-trapping structures based on optical interference effects combined with spectrum-splitting structures is theoretically investigated. Nearly perfect absorption over a broad spectrum range can be achieved in <100 nm thick films on top of a one-dimensional photonic crystal or metal films. This phenomenon can be attributed to interference induced photonic localization, which enhances the absorption and reduces the reflection of the films. Perfect solar absorption and low carrier thermalization loss can be achieved when the light-trapping structures with a wedge-shaped spacer layer or semiconductor films are combined with spectrum-splitting structures.
NASA Astrophysics Data System (ADS)
Fang, Yiqi; Lu, Qinghong; Wang, Xiaolei; Zhang, Wuhong; Chen, Lixiang
2017-02-01
The study of vortex dynamics is of fundamental importance in understanding the structured light's propagation behavior in the realm of singular optics. Here, combining with the large-angle holographic lithography in photoresist, a simple experiment to trace and visualize the vortex birth and splitting of light fields induced by various fractional topological charges is reported. For a topological charge M =1.76 , the recorded microstructures reveal that although it finally leads to the formation of a pair of fork gratings, these two vortices evolve asynchronously. More interestingly, it is observed on the submicron scale that high-order topological charges M =3.48 and 3.52, respectively, give rise to three and four characteristic forks embedded in the samples with one-wavelength resolution of about 450 nm. Numerical simulations based on orbital angular momentum eigenmode decomposition support well the experimental observations. Our method could be applied effectively to study other structured matter waves, such as the electron and neutron beams.
Mangrulkar, Priti A; Polshettiwar, Vivek; Labhsetwar, Nitin K; Varma, Rajender S; Rayalu, Sadhana S
2012-08-21
In the present investigation, hydrogen production via water splitting by nano-ferrites was studied using ethanol as the sacrificial donor and Pt as co-catalyst. Nano-ferrite is emerging as a promising photocatalyst with a hydrogen evolution rate of 8.275 μmol h(-1) and a hydrogen yield of 8275 μmol h(-1) g(-1) under visible light compared to 0.0046 μmol h(-1) for commercial iron oxide (tested under similar experimental conditions). Nano-ferrites were tested in three different photoreactor configurations. The rate of hydrogen evolution by nano-ferrite was significantly influenced by the photoreactor configuration. Altering the reactor configuration led to sevenfold (59.55 μmol h(-1)) increase in the hydrogen evolution rate. Nano-ferrites have shown remarkable stability in hydrogen production up to 30 h and the cumulative hydrogen evolution rate was observed to be 98.79 μmol h(-1). The hydrogen yield was seen to be influenced by several factors like photocatalyst dose, illumination intensity, irradiation time, sacrificial donor and presence of co-catalyst. These were then investigated in detail. It was evident from the experimental data that nano-ferrites under optimized reaction conditions and photoreactor configuration could lead to remarkable hydrogen evolution activity under visible light. Temperature had a significant role in enhancing the hydrogen yield.
Light-Driven Water Splitting by a Covalently Linked Ruthenium-Based Chromophore–Catalyst Assembly
Sherman, Benjamin D.; Xie, Yan; Sheridan, Matthew V.; Wang, Degao; Shaffer, David W.; Meyer, Thomas J.; Concepcion, Javier J.
2016-12-09
The preparation and characterization of new Ru(II) polypyridyl-based chromophore–catalyst assemblies, [(4,4'-PO_{3}H_{2}-bpy)_{2}Ru(4-Mebpy-4'-epic)Ru(bda)(pic)]^{2+} (1, bpy = 2,2'-bipyridine; 4-Mebpy-4'-epic = 4-(4-methylbipyridin-4'-yl-ethyl)-pyridine; bda = 2,2'-bipyridine-6,6'-dicarboxylate; pic = 4-picoline), and [(bpy)_{2}Ru(4-Mebpy-4'-epic)Ru(bda)(pic)]^{2+} (1') are described, as is the application of 1 in a dye-sensitized photoelectrosynthesis cell (DSPEC) for solar water splitting. Furthermore, on SnO_{2}/TiO_{2} core–shell electrodes in a DSPEC configuration with a Pt cathode, the chromophore–catalyst assembly undergoes light-driven water oxidation at pH 5.7 in a 0.1 M acetate buffer, 0.5 M in NaClO_{4}. We observed photocurrents of ~0.85 mA cm^{–2}, with illumination by a 100 mW cm^{–2} white light source, after 30 s under a 0.1 V vs Ag/AgCl applied bias with a faradaic efficiency for O_{2} production of 74% measured over a 5 min illumination period.
Light-Driven Water Splitting by a Covalently Linked Ruthenium-Based Chromophore–Catalyst Assembly
Sherman, Benjamin D.; Xie, Yan; Sheridan, Matthew V.; ...
2016-12-09
The preparation and characterization of new Ru(II) polypyridyl-based chromophore–catalyst assemblies, [(4,4'-PO3H2-bpy)2Ru(4-Mebpy-4'-epic)Ru(bda)(pic)]2+ (1, bpy = 2,2'-bipyridine; 4-Mebpy-4'-epic = 4-(4-methylbipyridin-4'-yl-ethyl)-pyridine; bda = 2,2'-bipyridine-6,6'-dicarboxylate; pic = 4-picoline), and [(bpy)2Ru(4-Mebpy-4'-epic)Ru(bda)(pic)]2+ (1') are described, as is the application of 1 in a dye-sensitized photoelectrosynthesis cell (DSPEC) for solar water splitting. Furthermore, on SnO2/TiO2 core–shell electrodes in a DSPEC configuration with a Pt cathode, the chromophore–catalyst assembly undergoes light-driven water oxidation at pH 5.7 in a 0.1 M acetate buffer, 0.5 M in NaClO4. We observed photocurrents of ~0.85 mA cm–2, with illumination by a 100 mW cm–2 white light source, after 30 s under amore » 0.1 V vs Ag/AgCl applied bias with a faradaic efficiency for O2 production of 74% measured over a 5 min illumination period.« less
Direct Water Splitting under Visible Light with a Nanostructured Photoanode and GaInP2 Photocathode
Wang, H.; Deutsch, T.; Turner, J.
2008-01-01
Thin films of hematite nanorod and GaInP2 were used for direct water splitting under visible light. In open circuit conditions, the potential of hematite shifted cathodically and that of GaInP2 anodically, which generated an open circuit voltage between the two electrodes. In short circuit condition, the combination of the two photoelectrodes can split water under visible light illumination, though with a very low current of {micro}A/cm2 level even at 1 W/cm2 light. By means of chopped light, we found that hematite nanorod has a low photocurrent, which is responsible for the low short circuit current of the 2-electrode combination. The low photoresponse of hematite nanorods is due to the recombination of photo- generated charges, low holes mobility, and short diffusion length.
Renger, Gernot
2012-08-01
The reactions of light induced oxidative water splitting were analyzed within the framework of the empirical rate constant-distance relationship of non-adiabatic electron transfer in biological systems (C. C. Page, C. C. Moser, X. Chen , P. L. Dutton, Nature 402 (1999) 47-52) on the basis of structure information on Photosystem II (PS II) (A. Guskov, A. Gabdulkhakov, M. Broser, C. Glöckner, J. Hellmich, J. Kern, J. Frank, W. Saenger, A. Zouni, Chem. Phys. Chem. 11 (2010) 1160-1171, Y. Umena, K. Kawakami, J-R Shen, N. Kamiya, Crystal structure of oxygen-evolving photosystem II at a resolution of 1.9Å. Nature 47 (2011) 55-60). Comparison of these results with experimental data leads to the following conclusions: 1) The oxidation of tyrosine Y(z) by the cation radical P680(+·) in systems with an intact water oxidizing complex (WOC) is kinetically limited by the non-adiabatic electron transfer step and the extent of this reaction is thermodynamically determined by relaxation processes in the environment including rearrangements of hydrogen bond network(s). In marked contrast, all Y(z)(ox) induced oxidation steps in the WOC up to redox state S(3) are kinetically limited by trigger reactions which are slower by orders of magnitude than the rates calculated for non-adiabatic electron transfer. 3) The overall rate of the triggered reaction sequence of Y(z)(ox) reduction by the WOC in redox state S(3) eventually leading to formation and release of O(2) is kinetically limited by an uphill electron transfer step. Alternative models are discussed for this reaction. The protein matrix of the WOC and bound water molecules provide an optimized dynamic landscape of hydrogen bonded protons for catalyzing oxidative water splitting energetically driven by light induced formation of the cation radical P680(+·). In this way the PS II core acts as a molecular machine formed during a long evolutionary process. This article is part of a Special Issue entitled: Photosynthesis Research
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.
NASA Astrophysics Data System (ADS)
Abe, Ryu
2011-10-01
The developments of water-splitting systems that can efficiently use visible light have been a major challenge for many years in order to realize efficient conversion of solar light. We have developed a new type of photocatalysis system that can split water into H2 and O2 under visible light irradiation, which was inspired by the two-step photoexcitation (Zscheme) mechanism of natural photosynthesis in green plants. In this system, the water splitting reaction is broken up into two stages: one for H2 evolution and the other for O2 evolution; these are combined by using a shuttle redox couple (Red/Ox) in the solution. The introduction of a Z-scheme mechanism reduces the energy required to drive each photocatalysis process, extending the usable wavelengths significantly (~460 nm for H2 evolution and ~600 nm for O2evolution) from that in conventional water splitting systems (~460 nm) based on one-step photoexcitation in single semiconductor material.
MWCNT/WO3 nanocomposite photoanode for visible light induced water splitting
NASA Astrophysics Data System (ADS)
Yousefzadeh, Samira; Reyhani, Ali; Naseri, Naimeh; Moshfegh, Alireza Z.
2013-08-01
The Multi-walled carbon nanotube (MWCNT)/WO3 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 WO3 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 WO3. The influence of different weight percentage (wt%) of MWCNT on WO3 photoactivity showed that the electron conductivity, charge transfer and electron life time had improved as compared with the pure WO3. Based on linear sweep voltammetry and chronoamperometry measurements, the (1 wt%) MWCNT/WO3 nanocomposite thin films photoanode has a maximum photocurrent density of ~4.5 A/m2 and electron life time of about 57 s.
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
Mir, Mustafa; Babacan, S Derin; Bednarz, Michael; Do, Minh N; Golding, Ido; Popescu, Gabriel
2012-01-01
Studying the 3D sub-cellular structure of living cells is essential to our understanding of biological function. However, tomographic imaging of live cells is challenging mainly because they are transparent, i.e., weakly scattering structures. Therefore, this type of imaging has been implemented largely using fluorescence techniques. While confocal fluorescence imaging is a common approach to achieve sectioning, it requires fluorescence probes that are often harmful to the living specimen. On the other hand, by using the intrinsic contrast of the structures it is possible to study living cells in a non-invasive manner. One method that provides high-resolution quantitative information about nanoscale structures is a broadband interferometric technique known as Spatial Light Interference Microscopy (SLIM). In addition to rendering quantitative phase information, when combined with a high numerical aperture objective, SLIM also provides excellent depth sectioning capabilities. However, like in all linear optical systems, SLIM's resolution is limited by diffraction. Here we present a novel 3D field deconvolution algorithm that exploits the sparsity of phase images and renders images with resolution beyond the diffraction limit. We employ this label-free method, called deconvolution Spatial Light Interference Tomography (dSLIT), to visualize coiled sub-cellular structures in E. coli cells which are most likely the cytoskeletal MreB protein and the division site regulating MinCDE proteins. Previously these structures have only been observed using specialized strains and plasmids and fluorescence techniques. Our results indicate that dSLIT can be employed to study such structures in a practical and non-invasive manner.
Gas-Phase Photochemical Overall H2 S Splitting by UV Light Irradiation.
Baldovi, Herme G; Albero, Josep; Ferrer, Belen; Mateo, Diego; Alvaro, Mercedes; García, Hermenegildo
2017-04-11
Splitting of hydrogen sulfide is achieved to produce value-added chemicals. Upon irradiation at 254 nm in the gas phase and in the absence of catalysts or photocatalysts at near room temperature, H2 S splits into stoichiometric amounts of H2 and S with a quantum efficiency close to 50 %. No influence of the presence of CH4 and CO2 (typical components in natural gas and biogas in which H2 S is an unwanted component) on the efficiency of overall H2 S splitting was observed. A mechanism for the H2 and S formation is proposed.
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.
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.
Light sources generating self-splitting beams and their propagation in non-Kolmogorov turbulence.
Mei, Zhangrong
2014-06-02
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.
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
2016-02-08
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.
NASA Astrophysics Data System (ADS)
Peng, Rui
Hydrogen generation from photocatalytic splitting of water is an ideal scenario that possesses promise for the sustainable development of human society and the establishment of the ultimate "green," infinitely renewable energy system. This work contains a series of novel photocatalytic systems in which the photoactive chromophores and/or the co-catalysts were incorporated into highly periodically cubic-phased MCM-48 mesoporous materials to achieve significantly higher photocatalytic efficiencies compared with conventional semiconductor photocatalysts. Cubic-phased MCM-48 mesoporous materials were chosen as supports to accommodate the photoactive species throughout the entire work. Several unique and iconic properties of these materials, such as large surface area, highly uniform mesoscale pores arrayed in a long-range periodicity, and an interconnected network of three-dimensional sets of pores that were recognized as positive parameters facilitated the photogenerated charge transfer and promoted the photocatalytic performance of the encapsulated photoactive species. It was validated that in the CdS/TiO2-incorporated MCM-48 photocatalytic system, the solar hydrogen conversion efficiency was prevalently governed by the photogenerated electron injection efficiency from the CdS conduction band to that of TiO2. The use of MCM-48 mesoporous host materials enabled the high and even dispersion of both CdS and TiO 2 so that the intimate and sufficient contact between CdS and TiO 2 was realized. In addition, with the presence of both TiO2 and MCM-48 mesoporous support, the photostability of CdS species was dramatically enhanced compared with that of bare CdS or CdS-incorporated MCM-48 photocatalysts. In advance, by loading the RuO2 co-catalyst into the CdS/TiO 2-incorporated MCM-48 photocatalytic system, the photocatalytic splitting of pure water to generate both hydrogen and oxygen under visible light illumination was achieved. In the various Pd-assisted, TiO2-incorporated
Asai, Rikako; Nemoto, Hiroaki; Jia, Qingxin; Saito, Kenji; Iwase, Akihide; Kudo, Akihiko
2014-03-07
IrO2-loaded SrTiO3 doped with rhodium and antimony synthesized by a conventional solid-state reaction splits water under visible light and simulated sunlight irradiation giving 0.1% of the apparent quantum yield at 420 nm. The response wavelength up to 500 nm is the longest among achieved photocatalytic water splitting with one-step photoexcitation.
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
2013-09-07
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.
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.
Splitting of high-Q Mie modes induced by light backscattering in silica microspheres
NASA Astrophysics Data System (ADS)
Weiss, D. S.; Sandoghdar, V.; Hare, J.; Lefèvre-Seguin, V.; Raimond, J.-M.; Haroche, S.
1995-09-01
We have observed that very high- Q Mie resonances in silica microspheres are split into doublets. This splitting is attributed to internal backscattering that couples the two degenerate whispering-gallery modes propagating in opposite directions along the sphere equator. We have studied this doublet structure by high-resolution spectroscopy. Time-decay measurements have also been performed and show a beat note corresponding to the coupling rate between the clockwise and counterclockwise modes. A simple model of coupled oscillators describes our data well, and the backscattering efficiency that we measure is consistent with what is observed in optical fibers.
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
From a philanthropic idea to building of civic hospital in Split in light of new archival evidence.
Brisky, Livia; Fatović-Ferencić, Stella
2006-02-01
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.
Jia, Qingxin; Iwashina, Katsuya; Kudo, Akihiko
2012-07-17
An efficient BiVO(4) thin film electrode for overall water splitting was prepared by dipping an F-doped SnO(2) (FTO) substrate electrode in an aqueous nitric acid solution of Bi(NO(3))(3) and NH(4)VO(3), and subsequently calcining it. X-ray diffraction of the BiVO(4) thin film revealed that a photocatalytically active phase of scheelite-monoclinic BiVO(4) was obtained. Scanning electron microscopy images showed that the surface of an FTO substrate was uniformly coated with the BiVO(4) film with 300-400 nm of the thickness. The BiVO(4) 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 BiVO(4) electrode improved the photoelectrochemical property. A photoelectrochemical cell consisting of the BiVO(4) 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 H(2) and O(2) 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 SrTiO(3)Rh photocathode and the BiVO(4) photoanode.
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...
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.
Isospin splittings in the light-baryon octet from lattice QCD and QED.
Borsanyi, Sz; Dürr, S; Fodor, Z; Frison, J; Hoelbling, C; Katz, S D; Krieg, S; Kurth, Th; Lellouch, L; Lippert, Th; Portelli, A; Ramos, A; Sastre, A; Szabo, K
2013-12-20
While electromagnetic and up-down quark mass difference effects on octet baryon masses are very small, they have important consequences. The stability of the hydrogen atom against beta decay is a prominent example. Here, we include these effects by adding them to valence quarks in a lattice QCD calculation based on Nf=2+1 simulations with five lattice spacings down to 0.054 fm, lattice sizes up to 6 fm, and average up-down quark masses all the way down to their physical value. This allows us to gain control over all systematic errors, except for the one associated with neglecting electromagnetism in the sea. We compute the octet baryon isomultiplet mass splittings, as well as the individual contributions from electromagnetism and the up-down quark mass difference. Our results for the total splittings are in good agreement with experiment.
Li, Xiaodong; Wang, Zhi; Zhang, Zemin; Chen, Lulu; Cheng, Jianli; Ni, Wei; Wang, Bin; Xie, Erqing
2015-03-16
The photoelectrochemical (PEC) water splitting is hampered by strong bonds of H2O molecules and low ionic conductivity of pure water. The photocatalysts dispersed in pure water can serve as a water activation agent, which provides an alternative pathway to overcome such limitations. Here we report that the light illuminated α-Fe2O3/Pt nanoparticles may produce a reservoir of reactive intermediates including H2O2, ·OH, OH(-) and H(+) capable of promoting the pure water reduction/oxidation half-reactions at cathode and highly photocatalytic-active TiO2/In2S3/AgInS2 photoanode, respectively. Remarkable photocurrent enhancement has been obtained with α-Fe2O3/Pt as water activation agent. The use of α-Fe2O3/Pt to promote the reactivity of pure water represents a new paradigm for reproducible hydrogen fuel provision by PEC water splitting, allowing efficient splitting of pure water without adding of corrosive chemicals or sacrificial agent.
Light Makes a Surface Banana-Bond Split: Photodesorption of Molecular Hydrogen from RuO _{2} (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 bond electron density, known as a Kubas complex, is the means by which H2 chemisorbs at Ru4+ 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 banana-bond involves an interband transition in RuO2 which effectively diminishes its Lewis acidity, and thereby weakening the Kubas complex. Such excitations are not expected to affect adsorbates on RuO2 given its metallic properties. Therefore, this common thermal co-catalyst employed in promoting water splitting is, itself, photo-active in the visible.
"DNA Origami Traffic Lights" with a Split Aptamer Sensor for a Bicolor Fluorescence Readout.
Walter, Heidi-Kristin; Bauer, Jens; Steinmeyer, Jeannine; Kuzuya, Akinori; Niemeyer, Christof M; Wagenknecht, Hans-Achim
2017-04-12
A split aptamer for adenosine triphosphate (ATP) was embedded as a recognition unit into two levers of a nanomechanical DNA origami construct by extension and modification of selected staple strands. An additional optical module in the stem of the split aptamer comprised two different cyanine-styryl dyes that underwent an energy transfer from green (donor) to red (acceptor) emission if two ATP molecules were bound as target molecule to the recognition module and thereby brought the dyes in close proximity. As a result, the ATP as a target triggered the DNA origami shape transition and yielded a fluorescence color change from green to red as readout. Conventional atomic force microscopy (AFM) images confirmed the topology change from the open form of the DNA origami in the absence of ATP into the closed form in the presence of the target molecule. The obtained closed/open ratios in the absence and presence of target molecules tracked well with the fluorescence color ratios and thereby validated the bicolor fluorescence readout. The correct positioning of the split aptamer as the functional unit farthest away from the fulcrum of the DNA origami was crucial for the aptasensing by fluorescence readout. The fluorescence color change allowed additionally to follow the topology change of the DNA origami aptasensor in real time in solution. The concepts of fluorescence energy transfer for bicolor readout in a split aptamer in solution, and AFM on surfaces, were successfully combined in a single DNA origami construct to obtain a bimodal readout. These results are important for future custom DNA devices for chemical-biological and bioanalytical purposes because they are not only working as simple aptamers but are also visible by AFM on the single-molecule level.
NASA Astrophysics Data System (ADS)
Cao, Dezhong; Xiao, Hongdi; Fang, Jiacheng; Liu, Jianqiang; Gao, Qingxue; Liu, Xiangdong; Ma, Jin
2017-01-01
Nanoporous (NP) GaN thin films, which were fabricated by an electrochemical etching method at different voltages, were used as photoelectrodes during photoelectrochemical (PEC) water splitting in 1 M oxalic acid solution. Upon illumination at a power density of 100 mW cm‑2 (AM 1.5), water splitting is observed in NP GaN thin films, presumably resulting from the valence band edge which is more positive than the redox potential of the oxidizing species. In comparison with NP GaN film fabricated at 8 V, NP GaN obtained at 18 V shows nearly twofold enhancement in photocurrent with the maximum photo-to-hydrogen conversion efficiency of 1.05% at ~0 V (versus Ag/AgCl). This enhancement could be explained with (i) the increase of surface area and surface states, and (ii) the decrease of resistances and carrier concentration in the NP GaN thin films. High stability of the NP GaN thin films during the PEC water splitting further confirms that the NP GaN thin film could be applied to the design of efficient solar cells and solar fuel devices.
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.
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.
Hung, Wei Hsuan; Lai, Sz Nian; Lo, An Ya
2015-04-29
The enhanced water splitting photocurrent has been observed through plasmonic mesoporous composite electrode TiO2-CMK-3/Ag under visible light irradiation. Strong light absorption achieved from the integrations of ordered mesoporous carbon (CMK-3) and silver plasmonic nanoparticles (NPs) layer in the TiO2, which significantly increased the effective optical depth of TiO2-CMK-3/Ag photoelectrode. The carbon-based CMK-3 also increased the surface wetting behavior and conductivity of the photoelectrodes, which resulted in a higher ion exchange rate and faster electron transport. The synthesis of high crystalline TiO2-CMK-3/Ag composite photocatalyst was verified by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Pronounced enhancement of light absorption of TiO2-CMK-3/Ag photoelectrode was confirmed by UV/vis spectrophotometers. Two orders of magnitude of the enhanced water splitting photocurrent were obtained in the TiO2-CMK-3/Ag composite photoelectrode with respect to TiO2 only. Finally, spatially resolved mapping photocurrents were also demonstrated in this study.
Dressed-photon–phonon (DPP)-assisted visible- and infrared-light water splitting
Yatsui, Takashi; Imoto, Tsubasa; Mochizuki, Takahiro; Kitamura, Kokoro; Kawazoe, Tadashi
2014-01-01
A dressed-phonon–phonon (DPP) assisted photocatalyst reaction was carried out to increase the visible light responsibility, where the photon energy of the radiation, which ranged from visible to infrared light is less than band gap energy of the photocatalyst (ZnO, 3.3 eV). The dependence of the photocurrent on excitation power indicated that two-step excitation occurred in DPP-assisted process. A cathodoluminescence measurement also supported the conclusion that the visible- and infrared-light excitation originated from DPP excitation, not from defect states in the ZnO nanorod photocatalyst. PMID:24691359
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
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
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
2015-11-10
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 In(3+)/Mo(6+) 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.
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.
Wang, H.; Deutsch, T.; Turner, J. A.
2008-01-01
A p-GaInP{sub 2} photocathode was paired with nanostructured hematite and tungsten trioxide photoanodes to investigate the utility of these systems for direct water splitting under visible light illumination. For the hematite system, under illumination at open-circuit conditions, the potential of hematite shifts cathodically and that of the GaInP{sub 2} shifts anodically. Under short-circuit condition and visible light illumination, the combination of the two photoelectrodes can split water, though with a very low rate of a few {micro}A/cm{sup 2} even at an intensity of 1 W/cm{sup 2}. It was determined that the very low photocurrent from the hematite nanorod photoelectrode limits the short-circuit current of the two-photoelectrode combination. Similar potential shifts were observed with the nanostructured WO{sub 3}/GaInP{sub 2} combination. However, at light intensities below 0.2 W/cm{sup 2}, the short-circuited combination would not split water due to an insufficient potential difference. Above 0.2 W/cm{sup 2}, the combination can split water under visible light, with {approx}20 {micro}A/cm{sup 2} obtained at 1 W/cm{sup 2}. A linear photocurrent-light intensity relationship was observed and was attributed to efficient charge transfer and a low recombination of the charge carriers. The bandgap and the associated absorption limit of WO{sub 3} remain a challenge for a higher efficiency system.
Origin of enhanced visible light driven water splitting by (Rh, Sb)-SrTiO3.
Modak, Brindaban; Ghosh, Swapan K
2015-06-21
A systematic calculation, using hybrid density functional theory, has been carried out to investigate the origin of the enhancement of photo-conversion efficiency of Rh-doped SrTiO3 with codoping of Sb. In the case of Rh-doped SrTiO3, partially unoccupied states are introduced above the valence band, thus lowering the hole oxidation at the valence band (VB) drastically, which explains the poor oxygen evolution activity of Rh-doped SrTiO3. We show that the partially occupied t2g subset of the Rh 4d orbital is completely filled in the presence of Sb due to the transfer of the extra electron to the Rh center. As a result, acceptor states are completely passivated in the case of (Rh, Sb)-codoped SrTiO3 and a continuous band structure with reduced band gap is formed, which is responsible for the observed enhanced photocatalytic activity of (Rh, Sb)-codoped SrTiO3. We have shown that the relative positions of the band edges of (Rh, Sb)-codoped SrTiO3 with respect to the water redox levels are in favor of the spontaneous release of both hydrogen and oxygen during water splitting, which is consistent with the experimental observation. We have also studied the effect of codoping in different proportions (1 : 2 and 2 : 1) of Rh and Sb. Although 1 : 2 (Rh, Sb)-codoping leads to the formation of a clean band structure with the reduction of the band gap by a larger extent, it shows lower photo-conversion efficiency due to its charge non-compensated nature. In addition, the presence of acceptor states above the VB limits the oxygen evolution efficiency of 2 : 1 (Rh, Sb)-codoped SrTiO3. Thus, the present approach successfully reproduces the experimental features of the Rh-monodoped as well as (Rh, Sb)-codoped SrTiO3 and also explains their origin.
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.
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.
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.
Nedbal, L; Gibas, C; Whitmarsh, J
1991-12-01
Photosystem II complexes of higher plants are structurally and functionally heterogeneous. While the only clearly defined structural difference is that Photosystem II reaction centers are served by two distinct antenna sizes, several types of functional heterogeneity have been demonstrated. Among these is the observation that in dark-adapted leaves of spinach and pea, over 30% of the Photosystem II reaction centers are unable to reduce plastoquinone to plastoquinol at physiologically meaningful rates. Several lines of evidence show that the impaired reaction centers are effectively inactive, because the rate of oxidation of the primary quinone acceptor, QA, is 1000 times slower than in normally active reaction centers. However, there are conflicting opinions and data over whether inactive Photosystem II complexes are capable of oxidizing water in the presence of certain artificial electron acceptors. In the present study we investigated whether inactive Photosystem II complexes have a functional water oxidizing system in spinach thylakoid membranes by measuring the flash yield of water oxidation products as a function of flash intensity. At low flash energies (less that 10% saturation), selected to minimize double turnovers of reaction centers, we found that in the presence of the artificial quinone acceptor, dichlorobenzoquinone (DCBQ), the yield of proton release was enhanced 20±2% over that observed in the presence of dimethylbenzoquinone (DMBQ). We argue that the extra proton release is from the normally inactive Photosystem II reaction centers that have been activated in the presence of DCBQ, demonstrating their capacity to oxidize water in repetitive flashes, as concluded by Graan and Ort (Biochim Biophys Acta (1986) 852: 320-330). The light saturation curves indicate that the effective antenna size of inactive reaction centers is 55±12% the size of active Photosystem II centers. Comparison of the light saturation dependence of steady state oxygen evolution
Katkovnik, Vladimir; Astola, Jaakko
2012-01-01
The 4f optical setup is considered with a wave field modulation by a spatial light modulator located in the focal plane of the first lens. Phase as well as amplitude of the wave field are reconstructed from noisy multiple-intensity observations. The reconstruction is optimal due to a constrained maximum likelihood formulation of the problem. The proposed algorithm is iterative with decoupling of the inverse of the forward propagation of the wave field and the filtering of phase and amplitude. The sparse modeling of phase and amplitude enables the advanced high-accuracy filtering and sharp imaging of the complex-valued wave field. Artifacts typical for the conventional algorithms (wiggles, ringing, waves, etc.) and attributed to optical diffraction can be suppressed by the proposed algorithm.
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
2015-08-03
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.
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.
Iwashina, Katsuya; Kudo, Akihiko
2011-08-31
A Rh-doped SrTiO(3) (SrTiO(3):Rh) photocatalyst electrode that was readily prepared by pasting SrTiO(3):Rh powder onto a transparent indium tin oxide electrode gave a cathodic photocurrent under visible-light irradiation (λ > 420 nm), indicating that the SrTiO(3):Rh photocatalyst electrode possessed p-type semiconductor character. The cathodic photocurrent increased with an increase in the amount of doped Rh up to 7 atom %. The incident-photon-to-current efficiency at 420 nm was 0.18% under an applied potential of -0.7 V vs Ag/AgCl for the SrTiO(3):Rh(7 atom %) photocatalyst electrode. The photocurrent was confirmed to be due to water splitting by analyzing the evolved H(2) and O(2). The water splitting proceeded with the application of an external bias smaller than 1.23 V versus a Pt counter electrode under visible-light irradiation and also using a solar simulator, suggesting that solar energy conversion should be possible with the present photoelectrochemical water splitting.
NASA Astrophysics Data System (ADS)
Wang, Meng; Ren, Feng; Zhou, Jigang; Cai, Guangxu; Cai, Li; Hu, Yongfeng; Wang, Dongniu; Liu, Yichao; Guo, Liejin; Shen, Shaohua
2015-08-01
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.
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
Zhang, Daoyu; Yang, Minnan
2013-11-14
The advantages of one-dimensional nanostructures, such as excellent charge separation and charge transport, low charge carrier recombination losses and so on, render them the photocatalysts of choice for many applications that exploit solar energy. In this work, based on very recently synthesized ultrathin anatase TiO2 nanowires, we explore the possibility of these wires as photocatalysts for photoelectrochemical water-splitting via the mono-doping (C, N, V, and Cr) and n-p codoping (C&V, C&Cr, N&V, and N&Cr) schemes. Our first-principles calculations predict that the C&Cr and C&V codoped ANWs may be strong candidates for photoelectrochemical water-splitting, because they have a substantially reduced band gap of 2.49 eV, appropriate band edge positions, no carrier recombination centers, and enhanced optical absorption in the visible light region.
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.
NASA Astrophysics Data System (ADS)
Higashi, Masanobu; Yamanaka, Yuta; Tomita, Osamu; Abe, Ryu
2015-10-01
A series of cation-doped BaTaO2N particle was synthesized to control the donor density in the bulk for improving the performance of photoelectrochemical water splitting on porous BaTaO2N photoanodes under visible light. Among the dopants (Mo6+, W6+, Zr4+, and Ti4+) examined, Mo6+ cations can be introduced into the Ta5+ site up to 5 mol. % without producing any impurity phases; the donor density of BaTaO2N was indeed increased significantly by introducing higher ratio of Mo6+ dopant. The porous photoanodes of Mo-doped BaTaO2N showed much higher photocurrent than others including undoped one and also exhibited much improved performance in photoelectrochemical water splitting into H2 and O2 after loaded with cobalt oxide cocatalyst and coupled with Pt counter electrode.
Zhang, Qiang; Hai, Zhenyin; Jian, Aoqun; Xu, Hongyan; Xue, Chenyang; Sang, Shengbo
2016-01-01
p-Co3O4/n-TiO2 nanoparticles (~400 nm) for photocatalysis were prepared via carbon assisted method and sol-gel method in this work. The paper also studied the application of visible light illuminated p-Co3O4/n-TiO2 nanocomposites cocatalyst to the overall pure water splitting into H2 and O2. In addition, the H2 evolution rate of the p-Co3O4/n-TiO2 nanocomposites is 25% higher than that of the pure Co3O4 nanoparticles. Besides, according to the results of the characterizations, the scheme of visible light photocatalytic water splitting is proposed, the Co3O4 of the nanocomposites is excited by visible light, and the photo-generated electrons and holes existing on the conduction band of Co3O4 and valence band of TiO2 have endowed the photocatalytic evolution of H2 and O2 with higher efficiency. The optimal evolution rate of H2 and O2 is 8.16 μmol/h·g and 4.0 μmol/h·g, respectively. PMID:28335266
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.
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.
Azzam, R M A
2016-05-01
The simplified explicit expressions derived by Andersen [J. Opt. Soc. Am. A33, 984 (2016)JOAOD60740-323210.1364/JOSAA.32.000984], that relate to angularly symmetric beam splitting by reflection and refraction at an air-dielectric interface recently described by Azzam [J. Opt. Soc. Am. A32, 2436 (2015)JOAOD60740-323210.1364/JOSAA.32.002436], are welcome. A few additional remarks are also included in my reply to Andersen's comment.
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
2013-01-09
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.
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)
Ziegler, Jürgen; Yang, Florent; Wagner, Stephan; Kaiser, Bernhard; Jaegermann, Wolfram; Urbain, Félix; Becker, Jan-Philipp; Smirnov, Vladimir; Finger, Friedhelm
2016-12-01
TiO2 is a common protection layer on semiconductor electrodes for photoelectrochemical water splitting. We investigate the interface formation of TiO2 on amorphous silicon tandem solar cells by X-ray photoelectron spectroscopy. In order to optimize the contact properties, we prepare TiOx interface layers with various oxygen content by reactive magnetron sputter deposition. We observe, that a TiOx interface layer can reduce the silicon oxide growth during the film deposition on the amorphous silicon, but it forms a non-ohmic contact. The electrochemical investigation shows, that the benefit due to the reduction of the silicon oxide is counteracted by the unfavorable contact formation of TiOx interface layers prepared with low oxygen content.
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
NASA Astrophysics Data System (ADS)
Bergmann, Uwe
2010-02-01
Arguably the most important chemical reaction on earth is the photosynthetic splitting of water to molecular oxygen by the Mn-containing oxygen-evolving complex (Mn-OEC) in the protein known as photosystem II (PSII). It is this reaction which has, over the course of some 3.8 billion years, gradually filled our atmosphere with O2 and consequently enabled and sustained the evolution of complex aerobic life. Coupled to the reduction of carbon dioxide, biological photosynthesis contributes foodstuffs for nutrition while recycling CO2 from the atmosphere and replacing it with O2. By utilizing sunlight to power these energy-requiring reactions, photosynthesis also serves as a model for addressing societal energy needs as we enter an era of diminishing fossil hydrocarbon resources. Understanding, at the molecular level, the dynamics and mechanism of how nature has solved this problem is of fundamental importance and could be critical to aid in the design of manufactured devices to accomplish the conversion of sunlight into useful electrochemical energy and transportable fuel in the foreseeable future. In order to understand the photosynthetic splitting of water by the Mn-OEC we need to be able to follow the reaction in real time at an atomic level. A powerful probe to study the electronic and molecular structure of the Mn-OEC is x-ray spectroscopy. Here, in particular x-ray emission spectroscopy (XES) has two crucial qualities for LCLS based time-dependent pump-probe studies of the Mn-OEC: a) it directly probes the Mn oxidation state and ligation, b) it can be performed with wavelength dispersive optics to avoid the necessity of scanning in pump probe experiments. Recent results and the planned time dependent experiments at LCLS will be discussed. )
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.
Liu, J.W.; Chen, G. . E-mail: gchen@hit.edu.cn; Li, Z.H.; Zhang, Z.G.
2006-12-15
Cr-doped SrTi{sub 1-} {sub x} Cr {sub x} O{sub 3} (x=0.00, 0.02, 0.05, 0.10) powders, prepared by solvothermal method, were further characterized by ultraviolet-visible (UV-vis) absorption spectroscopy. The UV-vis spectra indicate that the SrTi{sub 1-} {sub x} Cr {sub x} O{sub 3} powders can absorb not only UV light like pure SrTiO{sub 3} powder but also the visible-light spectrum ({lambda}>420 nm). The results of density functional theory (DFT) calculation illuminate that the visible-light absorption bands in the SrTi{sub 1-} {sub x} Cr {sub x} O{sub 3} catalyst are attributed to the band transition from the Cr 3d to the Cr 3d+Ti 3d hybrid orbital. The photocatalytic activities of chromium-doped SrTiO{sub 3} both under UV and visible light are increased with the increase in the amounts of chromium. -- Graphical abstract: SrTi{sub 1-} {sub x} Cr {sub x} O{sub 3} powders, prepared by solvothermal method, can absorb not only UV light like pure SrTiO{sub 3} powder but also the visible-light spectrum ({lambda}>420 nm). The results of DFT calculation illuminate that the visible-light absorption bands in the SrTi{sub 1-} {sub x} Cr {sub x} O{sub 3} catalyst are attributed to the band transition from the Cr 3d to the Cr 3d+Ti 3d hybrid orbital.
NASA Astrophysics Data System (ADS)
Yang, Ke; Li, Dong-Feng; Huang, Wei-Qing; Xu, Liang; Huang, Gui-Fang; Wen, Shuangchun
2017-01-01
Enhanced visible-light photocatalytic activity of transition-metal-doped ceria (CeO2) nanomaterials has experimentally been demonstrated, whereas there are very few reports mentioning the mechanism of this behavior. Here, we use first-principles calculations to explore the origin of enhanced photocatalytic performance of CeO2 doped with transition metal impurities (Fe, Cr and Co). When a transition metal atom substitutes a Ce atom into CeO2, t 2g and e g levels of 3 d orbits appear in the middle of band gap owing to the effect of cubic ligand field, and the former is higher than latter. Interestingly, t 2g subset of FeCe (CoCe and CrCe)-Vo-CeO2 splits into two parts: one merges into the conduction band, the other as well as e g will remain in the gap, because O vacancy defect adjacent to transition metal atom will break the symmetry of cubic ligand field. These e g and t 2g levels in the band gap are beneficial for absorbing visible-light and enhancing quantum efficiency because of forbidden transition, which is one key factor for enhanced visible-light photocatalytic activity. The band gap narrowing also leads to a redshift of optical absorbance and high photoactivity. These findings can rationalize the available experimental results and provide some new insights for designing CeO2-based photocatalysts with high photocatalytic performance.
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
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.
Vectorized Sparse Elimination.
1984-03-01
Grids," Proc. 6th Symposium on Reservoir Simulation , New Orleans, Feb. 1-2, 1982, pp. 489-506. [51 Arya, S., and D. A. Calahan, "Optimal Scheduling of...of Computer Architecture on Direct Sparse Matrix Routines in Petroleum Reservoir Simulation ," Sparse Matrix Symposium, Fairfield Glade, TE, October
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)
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.
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.
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.
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.
Sjöholm, Johannes; Styring, Stenbjörn; Havelius, Kajsa G V; Ho, Felix M
2012-03-13
Cryogenic illumination of Photosystem II (PSII) can lead to the trapping of the metastable radical Y(Z)(•), the radical form of the redox-active tyrosine residue D1-Tyr161 (known as Y(Z)). Magnetic interaction between this radical and the CaMn(4) cluster of PSII gives rise to so-called split electron paramagnetic resonance (EPR) signals with characteristics that are dependent on the S state. We report here the observation and characterization of a split EPR signal that can be directly induced from PSII centers in the S(2) state through visible light illumination at 10 K. We further show that the induction of this split signal takes place via a Mn-centered mechanism, in the same way as when using near-infrared light illumination [Koulougliotis, D., et al. (2003) Biochemistry 42, 3045-3053]. On the basis of interpretations of these results, and in combination with literature data for other split signals induced under a variety of conditions (temperature and light quality), we propose a unified model for the mechanisms of split signal induction across the four S states (S(0), S(1), S(2), and S(3)). At the heart of this model is the stability or instability of the Y(Z)(•)(D1-His190)(+) pair that would be formed during cryogenic oxidation of Y(Z). Furthermore, the model is closely related to the sequence of transfers of protons and electrons from the CaMn(4) cluster during the S cycle and further demonstrates the utility of the split signals in probing the immediate environment of the oxygen-evolving center in PSII.
Evolving sparse stellar populations
NASA Astrophysics Data System (ADS)
Bruzual, Gustavo; Gladis Magris, C.; Hernández-Pérez, Fabiola
2017-03-01
We examine the role that stochastic fluctuations in the IMF and in the number of interacting binaries have on the spectro-photometric properties of sparse stellar populations as a function of age and metallicity.
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.
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.
Grassmannian sparse representations
NASA Astrophysics Data System (ADS)
Azary, Sherif; Savakis, Andreas
2015-05-01
We present Grassmannian sparse representations (GSR), a sparse representation Grassmann learning framework for efficient classification. Sparse representation classification offers a powerful approach for recognition in a variety of contexts. However, a major drawback of sparse representation methods is their computational performance and memory utilization for high-dimensional data. A Grassmann manifold is a space that promotes smooth surfaces where points represent subspaces and the relationship between points is defined by the mapping of an orthogonal matrix. Grassmann manifolds are well suited for computer vision problems because they promote high between-class discrimination and within-class clustering, while offering computational advantages by mapping each subspace onto a single point. The GSR framework combines Grassmannian kernels and sparse representations, including regularized least squares and least angle regression, to improve high accuracy recognition while overcoming the drawbacks of performance and dependencies on high dimensional data distributions. The effectiveness of GSR is demonstrated on computationally intensive multiview action sequences, three-dimensional action sequences, and face recognition datasets.
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.
Wang, Limin; Cao, Bingfei; Kang, Wei; Hybertsen, Mark; Maeda, Kazuhiko; Domen, Kazunari; Khalifah, Peter G
2013-08-19
Two new metal oxide semiconductors belonging to the Ag-Bi-M-O (M = Nb, Ta) chemical systems have been synthesized as candidate compounds for driving overall water splitting with visible light on the basis of cosubstitution of Ag and Bi on the A-site position of known Ca2M2O7 pyrochlores. The low-valence band edge energies of typical oxide semiconductors prevents direct water splitting in compounds with band gaps below 3.0 eV, a limitation which these compounds are designed to overcome through the incorporation of low-lying Ag 4d(10) and Bi 6s(2) states into compounds of nominal composition "AgBiM2O7". It was found that the "AgBiTa2O7" pyrochlores are in fact a solid solution with an approximate range of Ag(x)Bi(5/6)Ta2O(6.25+x/2) with 0.5 < x < 1. The structure of Ag4/5Bi5/6Ta2O6.65 was determined from the refinement of time-of-flight neutron diffraction data and was found to be a cubic pyrochlore with a = 10.52268(2) Å and a volume of 1165.143(6) Å(3). The closely related compound, AgBiNb2O7, appears to have an integer stoichiometry and to adopt an orthorhombically distorted pyrochlore-related structure with a subcell of a = 7.50102(8) Å, b = 7.44739(7) Å, c = 10.5788(1) Å, and V = 590.93(2) Å(3). Density functional theory-based calculations predict this distortion should result from A-site cation ordering. Fits to UV-vis diffuse reflectance data suggest that AgBiNb2O7 and "AgBiTa2O7" are both visible-light-absorbing semiconductors with the onset of strong direct absorption at 2.72 and 2.96 eV, respectively. Electronic structure calculations for an ordered AgBiNb2O7 structure show that the band gap reduction and the elevation of the valence band primarily result from hybridized Ag d(10)-O 2p orbitals that lie at higher energy than the normal O 2p states in typical pyrochlore oxides. While the minimum energy gap is direct in the band structure, the lowest energy dipole allowed optical transitions start about 0.2 eV higher in energy than the minimum energy
Multiple Sparse Representations Classification
Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik
2015-01-01
Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and
Deshpande, Aparna; Shah, Pallavi; Gholap, R S; Gupta, Narendra M
2009-05-01
Nano-composite CdSZnS moieties coated over polyester strip were found to exhibit better visible-light-mediated photo-activity for splitting of water, as compared to corresponding pure CdS or ZnS containing coupons. This increase in activity depended upon the mol ratio of the two component sulphides in a particular sample. HRTEM experiments revealed the presence of 1-3 nm size CdS particles embedded over larger size ZnS clusters, the composite samples thus functioning as a highly dispersed guest-host system. In the case of CdS and ZnS dispersed individually over polyester, average crystallite size was found to be around 5 and 15 nm, respectively. A blue shift was observed in the UV-vis absorption spectrum of CdS on addition of ZnS, in conformation with the quantum size effects. Powder XRD, electron diffraction and XPS studies showed that the nanocomposites were comprised of the face-centered cubic (alpha) phases of both CdS and ZnS in a close contact with each other. At the same time, certain solid solution phases, i.e. Cd(1-x)Zn(x)S, were generated at the interfaces of these two semiconductors. Our study demonstrates that the increase in the number of reaction sites due to smaller size of CdS particles and the micro-structural properties associated with the nanostructured CdS or CdS/ZnS interfaces may together play a vital role in the augmented catalytic activity of CdSZnS composite photocatalysts.
Artero, Vincent; Chavarot-Kerlidou, Murielle; Fontecave, Marc
2011-08-01
The future of energy supply depends on innovative breakthroughs regarding the design of cheap, sustainable, and efficient systems for the conversion and storage of renewable energy sources, such as solar energy. The production of hydrogen, a fuel with remarkable properties, through sunlight-driven water splitting appears to be a promising and appealing solution. While the active sites of enzymes involved in the overall water-splitting process in natural systems, namely hydrogenases and photosystem II, use iron, nickel, and manganese ions, cobalt has emerged in the past five years as the most versatile non-noble metal for the development of synthetic H(2)- and O(2)-evolving catalysts. Such catalysts can be further coupled with photosensitizers to generate photocatalytic systems for light-induced hydrogen evolution from water.
Kato, Takaaki; Hakari, Yuichiro; Ikeda, Satoru; Jia, Qingxin; Iwase, Akihide; Kudo, Akihiko
2015-03-19
Upon forming a solid solution between CuGaS2 and ZnS, we have successfully developed a highly active (CuGa)(1-x)Zn(2x)S2 photocatalyst for H2 evolution in the presence of sacrificial reagents under visible light irradiation. The Ru-loaded (CuGa)0.8Zn0.4S2 functioned as a H2-evolving photocatalyst in a Z-scheme system with BiVO4 of an O2-evolving photocatalyst and Co complexes of an electron mediator. The Z-scheme system split water into H2 and O2 under visible light and simulated sunlight irradiation. The (CuGa)(1-x)Zn(2x)S2 possessed a p-type semiconductor character. The photoelectrochemical cell with a Ru-loaded (CuGa)0.5ZnS2 photocathode and a CoO(x)-modified BiVO4 photoanode split water even without applying an external bias. Thus, we successfully demonstrated that the metal sulfide material group can be available for Z-scheme and electrochemical systems to achieve solar water splitting into H2 and O2.
Sparse inpainting and isotropy
NASA Astrophysics Data System (ADS)
Feeney, Stephen M.; Marinucci, Domenico; McEwen, Jason D.; Peiris, Hiranya V.; Wandelt, Benjamin D.; Cammarota, Valentina
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.
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.
Yin, Junming; Chen, Xi; Xing, Eric P.
2016-01-01
We consider the problem of sparse variable selection in nonparametric additive models, with the prior knowledge of the structure among the covariates to encourage those variables within a group to be selected jointly. Previous works either study the group sparsity in the parametric setting (e.g., group lasso), or address the problem in the nonparametric setting without exploiting the structural information (e.g., sparse additive models). In this paper, we present a new method, called group sparse additive models (GroupSpAM), which can handle group sparsity in additive models. We generalize the ℓ1/ℓ2 norm to Hilbert spaces as the sparsity-inducing penalty in GroupSpAM. Moreover, we derive a novel thresholding condition for identifying the functional sparsity at the group level, and propose an efficient block coordinate descent algorithm for constructing the estimate. We demonstrate by simulation that GroupSpAM substantially outperforms the competing methods in terms of support recovery and prediction accuracy in additive models, and also conduct a comparative experiment on a real breast cancer dataset.
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.
Flexible sparse regularization
NASA Astrophysics Data System (ADS)
Lorenz, Dirk A.; Resmerita, Elena
2017-01-01
The seminal paper of Daubechies, Defrise, DeMol made clear that {{\\ell }}p spaces with p\\in [1,2) and p-powers of the corresponding norms are appropriate settings for dealing with reconstruction of sparse solutions of ill-posed problems by regularization. It seems that the case p = 1 provides the best results in most of the situations compared to the cases p\\in (1,2). An extensive literature gives great credit also to using {{\\ell }}p spaces with p\\in (0,1) together with the corresponding quasi-norms, although one has to tackle challenging numerical problems raised by the non-convexity of the quasi-norms. In any of these settings, either superlinear, linear or sublinear, the question of how to choose the exponent p has been not only a numerical issue, but also a philosophical one. In this work we introduce a more flexible way of sparse regularization by varying exponents. We introduce the corresponding functional analytic framework, that leaves the setting of normed spaces but works with so-called F-norms. One curious result is that there are F-norms which generate the ℓ 1 space, but they are strictly convex, while the ℓ 1-norm is just convex.
Photoelectrochemical water-splitting systems
Turner, J.A.; Kocha, S.S.
1995-10-01
Photochemical water-splitting is the process where an illuminated semiconductor is used to decompose water into its components, hydrogen and oxygen. Light, incident on a semiconductor electrode, splits water directly. A one-step monolithic system such as this eliminates the need to generate electricity externally and subsequently feed it to an electrolyser. Combining the electrolyser with the PV system eliminates one of the high cost components of a PV-electrolysis hydrogen generation system. Since external wiring is not used, only the piping necessary for the transport of hydrogen to an external storage system or gas pipeline is required. This paper will discuss the current technical status of direct conversion photoelectrochemical (PEC) water-splitting systems.
Kobayashi, Ryoya; Takashima, Toshihiro; Tanigawa, Satoshi; Takeuchi, Shugo; Ohtani, Bunsho; Irie, Hiroshi
2016-10-12
We recently reported the synthesis of a solid-state heterojunction photocatalyst consisting of zinc rhodium oxide (ZnRh2O4) and bismuth vanadium oxide (Bi4V2O11), which functioned as hydrogen (H2) and oxygen (O2) evolution photocatalysts, respectively, connected with silver (Ag). Polycrystalline Bi4V2O11 (p-Bi4V2O11) powders were utilized to form ZnRh2O4/Ag/p-Bi4V2O11, which was able to photocatalyze overall pure-water splitting under red-light irradiation with a wavelength of 700 nm (R. Kobayashi et al., J. Mater. Chem. A, 2016, 4, 3061). In the present study, we replaced p-Bi4V2O11 with a powder obtained by pulverizing single crystals of Bi4V2O11 (s-Bi4V2O11) to form ZnRh2O4/Ag/s-Bi4V2O11, and demonstrated that this heterojunction photocatalyst had enhanced water-splitting activity. In addition, ZnRh2O4/Ag/s-Bi4V2O11 was able to utilize nearly the entire range of visible light up to a wavelength of 740 nm. These properties were attributable to the higher O2 evolution activity of s-Bi4V2O11.
Percolation on Sparse Networks
NASA Astrophysics Data System (ADS)
Karrer, Brian; Newman, M. E. J.; Zdeborová, Lenka
2014-11-01
We study percolation on networks, which is used as a model of the resilience of networked systems such as the Internet to attack or failure and as a simple model of the spread of disease over human contact networks. We reformulate percolation as a message passing process and demonstrate how the resulting equations can be used to calculate, among other things, the size of the percolating cluster and the average cluster size. The calculations are exact for sparse networks when the number of short loops in the network is small, but even on networks with many short loops we find them to be highly accurate when compared with direct numerical simulations. By considering the fixed points of the message passing process, we also show that the percolation threshold on a network with few loops is given by the inverse of the leading eigenvalue of the so-called nonbacktracking matrix.
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.
Yuan, Qichen; Liu, Dong; Zhang, Ning; Ye, Wei; Ju, Huanxin; Shi, Lei; Long, Ran; Zhu, Junfa; Xiong, Yujie
2017-03-15
Z-scheme water splitting is a promising approach based on high-performance photocatalysis by harvesting broadband solar energy. Its efficiency depends on the well-defined interfaces between two semiconductors for the charge kinetics and their exposed surfaces for chemical reactions. Herein, we report a facile cation-exchange approach to obtain compounds with both properties without the need for noble metals by forming Janus-like structures consisting of γ-MnS and Cu7 S4 with high-quality interfaces. The Janus-like γ-MnS/Cu7 S4 structures displayed dramatically enhanced photocatalytic hydrogen production rates of up to 718 μmol g(-1) h(-1) under full-spectrum irradiation. Upon further integration with an MnOx oxygen-evolution cocatalyst, overall water splitting was accomplished with the Janus structures. This work provides insight into the surface and interface design of hybrid photocatalysts, and offers a noble-metal-free approach to broadband photocatalytic hydrogen production.
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)
Inoue, Tomoyuki; Toprasertpong, Kasidit; Delamarre, Amaury; Watanabe, Kentaroh; Paire, Myriam; Lombez, Laurent; Guillemoles, Jean-François; Sugiyama, Masakazu; Nakano, Yoshiaki
2016-03-01
Insertion of InGaAs/GaAsP strain-balanced multiple quantum wells (MQWs) into i-regions of GaAs p-i-n solar cells show several advantages against GaAs bulk p-i-n solar cells. Particularly under high-concentration sunlight condition, enhancement of the open-circuit voltage with increasing concentration ratio in thin-barrier MQW cells has been reported to be more apparent than that in GaAs bulk cells. However, investigation of the MQW cell mechanisms in terms of I-V characteristics under high-concentration sunlight suffers from the increase in cell temperature and series resistance. In order to investigate the mechanism of the steep enhancement of open-circuit voltage in MQW cells under high-concentration sunlight without affected by temperature, the quasi-Fermi level splitting was evaluated by analyzing electroluminescence (EL) from a cell. Since a cell under current injection with a density Jinjhas similar excess carrier density to a cell under concentrated sunlight with an equivalent short-circuit current Jsc = Jinj, EL measurement with varied Jinj can approximately evaluate a cell performance under a variety of concentration ratio. In addition to the evaluation of quasi-Fermi level splitting, the external luminescence efficiency was also investigated with the EL measurement. The MQW cells showed higher external luminescence efficiency than the GaAs reference cells especially under high-concentration condition. The results suggest that since the MQW region can trap and confine carriers, the localized excess carriers inside the cells make radiative recombination more dominant.
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.
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.
Cao, Zhanli; Li, Zhendong; Wang, Fan; Liu, Wenjian
2017-02-01
The spin-separated exact two-component (X2C) relativistic Hamiltonian [sf-X2C+so-DKHn, J. Chem. Phys., 2012, 137, 154114] is combined with the equation-of-motion coupled-cluster method with singles and doubles (EOM-CCSD) for the treatment of spin-orbit splittings of open-shell molecular systems. Scalar relativistic effects are treated to infinite order from the outset via the spin-free part of the X2C Hamiltonian (sf-X2C), whereas the spin-orbit couplings (SOC) are handled at the CC level via the first-order Douglas-Kroll-Hess (DKH) type of spin-orbit operator (so-DKH1). Since the exponential of single excitations, i.e., exp(T1), introduces sufficient spin orbital relaxations, the inclusion of SOC at the CC level is essentially the same in accuracy as the inclusion of SOC from the outset in terms of the two-component spinors determined variationally by the sf-X2C+so-DKH1 Hamiltonian, but is computationally more efficient. Therefore, such an approach (denoted as sf-X2C-EOM-CCSD(SOC)) can achieve uniform accuracy for the spin-orbit splittings of both light and heavy elements. For light elements, the treatment of SOC can even be postponed until the EOM step (denoted as sf-X2C-EOM(SOC)-CCSD), so as to further reduce the computational cost. To reveal the efficacy of sf-X2C-EOM-CCSD(SOC) and sf-X2C-EOM(SOC)-CCSD, the spin-orbit splittings of the (2)Π states of monohydrides up to the sixth row of the periodic table are investigated. The results show that sf-X2C-EOM-CCSD(SOC) predicts very accurate results (within 5%) for elements up to the fifth row, whereas sf-X2C-EOM(SOC)-CCSD is useful only for light elements (up to the third row but with some exceptions). For comparison, the sf-X2C-S-TD-DFT-SOC approach [spin-adapted open-shell time-dependent density functional theory, Mol. Phys., 2013, 111, 3741] is applied to the same systems. The overall accuracy (1-10%) is satisfactory.
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.
Sparse Methods for Biomedical Data.
Ye, Jieping; Liu, Jun
2012-06-01
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 [Formula: see text] 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.
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
Zhang, Jian; Zhu, Wenfeng; Liu, Xiaoheng
2014-06-28
CdS quantum dot/vermiculite (CdS/VMT) nanocomposites have been synthesized via a facile one-step method and characterized by X-ray diffraction, UV-vis diffuse reflection spectroscopy, X-ray photoelectron spectroscopy, and transmission electron microscopy. The photocatalytic hydrogen generation activities of these samples were evaluated using Na2S and Na2SO3 as sacrificial reagents in water under visible-light illumination (λ ≥ 420 nm). The most important aspect of this work is the use of natural products (VMT) as host photocatalysts. The effect of CdS content on the rate of visible light photocatalytic hydrogen generation was investigated for different CdS loadings. The synergistic effect of VMT and CdS quantum dots (QDs) leads to efficient separation of the photogenerated charge carriers and, consequently, enhances the visible light photocatalytic hydrogen production activity of the photocatalyst. The CdS/VMT composite with an optimal ratio of 5% exhibits the highest hydrogen evolution rate of 92 μmol h(-1) under visible light irradiation and the highest apparent quantum efficiency of 17.7% at 420 nm. A possible photocatalytic mechanism of the CdS/VMT nanocomposite is proposed and corroborated by photoelectrochemical curves.
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
Bhirud, Ashwini P; Sathaye, Shivaram D; Waichal, Rupali P; Ambekar, Jalindar D; Park, Chan-J; Kale, Bharat B
2015-03-21
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.
Photocatalytic water splitting
NASA Astrophysics Data System (ADS)
Kuo, Yenting
New photocatalystic materials Ti-In oxy(nitride) and nanosized Ru-loaded strontium titanate doped with Rh (Ru/SrTiO3:Rh) have been synthesized. The textural and surface characteristic properties were studied by nitrogen BET analysis, diffuse reflectance UV-vis spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, scanning electron microscopy and powder XRD. The photocatalytic properties were enhanced by the binary metal oxides of titanium dioxide and indium oxide. The XRD patterns confirmed the oxygen exchange between two metal oxides during the synthesis. Moreover, the presence of titanium dioxide can help the stabilization of InN during hot NH3(g) treatment. On the other hand, the particle sizes of aerogel prepared Ru/SrTiO3:Rh varied from 12 to 25 nm depended on different Rh doping. A mixture of ethanol and toluene was found to be the best binary solvent for supercritical drying, which yielded a SrTiO3 sample with a surface area of 130 m2/g and an average crystallite size of 6 nm. Enhanced photocatalytic hydrogen production under UV-vis light irradiation was achieved by ammonolysis of intimately mixed titanium dioxide and indium oxide at high temperatures. Gas chromatography monitored steadily the formation of hydrogen when sacrificial (methanol or ethanol) were present. XRD patterns confirmed that the photocatalysts maintain crystalline integrity before and after water splitting experiments. Moreover, the presence of InN may be crucial for the increase of hydrogen production activities. These Ru/SrTiO3:Rh photocatalysts have been studied for photocatalytic hydrogen production under visible light. The band gap of the bulk SrTiO 3 (3.2 eV) does not allow response to visible light. However, after doping with rhodium and loaded with ruthenium, the modified strontium titanates can utilize light above 400 nm due to the formation of valence band or electron donor levels inside of the band gap. Moreover, the surface areas of these
Wang, Ruosong; Xu, Xiaoxue; Zhang, Yi; Chang, Zhimin; Sun, Zaicheng; Dong, Wen-Fei
2015-07-07
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.
Benzi, Michele; Evans, Thomas M.; Hamilton, Steven P.; ...
2017-03-05
Here, we consider hybrid deterministic-stochastic iterative algorithms for the solution of large, sparse linear systems. Starting from a convergent splitting of the coefficient matrix, we analyze various types of Monte Carlo acceleration schemes applied to the original preconditioned Richardson (stationary) iteration. We expect that these methods will have considerable potential for resiliency to faults when implemented on massively parallel machines. We also establish sufficient conditions for the convergence of the hybrid schemes, and we investigate different types of preconditioners including sparse approximate inverses. Numerical experiments on linear systems arising from the discretization of partial differential equations are presented.
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
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.
Sparse and powerful cortical spikes.
Wolfe, Jason; Houweling, Arthur R; Brecht, Michael
2010-06-01
Activity in cortical networks is heterogeneous, sparse and often precisely timed. The functional significance of sparseness and precise spike timing is debated, but our understanding of the developmental and synaptic mechanisms that shape neuronal discharge patterns has improved. Evidence for highly specialized, selective and abstract cortical response properties is accumulating. Singe-cell stimulation experiments demonstrate a high sensitivity of cortical networks to the action potentials of some, but not all, single neurons. It is unclear how this sensitivity of cortical networks to small perturbations comes about and whether it is a generic property of cortex. The unforeseen sensitivity to cortical spikes puts serious constraints on the nature of neural coding schemes.
NASA Astrophysics Data System (ADS)
Vernon, C. G.
2016-09-01
Preface; 1. Historical; 2. Waves and wave-motion; 3. The behaviour of ripples; 4. The behaviour of light; 5. Refraction through glass blocks and prisms; 6. The imprinting of curvatures; 7. Simple mathematical treatment; 8. More advanced mathematical treatment; 9. The velocity of light; 10. The spectrum and colour; 11. Geometrical optics; 12. The eye and optical instruments; 13. Sources of light; 14. Interference, diffraction and polarisation; 15. Suggestions for class experiments; Index.
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.
Solar hydrogen production on some water splitting photocatalysts
NASA Astrophysics Data System (ADS)
Takata, Tsuyoshi; Hisatomi, Takashi; Domen, Kazunari
2016-09-01
Photocatalytic overall water splitting into H2 and O2 is expected to be a promising method for the efficient utilization of solar energy. The design of optimal photocatalyst structures is a key to efficient overall water splitting, and the development of photocatalysts which can efficiently convert large portion of visible light spectrum has been required. Recently, a series of complex perovskite type transition metal oxynitrides, LaMgxT 1-xO1+3xN2-3x, was developed as photocatalysts for direct water splitting operable at wide wavelength of visible light. In addition two-step excitation water splitting via a novel photocatalytic device termed as photocatalyst sheet was developed. This consists of two types of semiconductors (hydrogen evolution photocatalyst and oxygen evolution photocatalyst) particles embedded in a conductive layer, and showed high efficiency for overall water splitting. These recent advances in photocatalytic water splitting were introduced.
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 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.
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 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
Sparse Regression by Projection and Sparse Discriminant Analysis.
Qi, Xin; Luo, Ruiyan; Carroll, Raymond J; Zhao, Hongyu
2015-04-01
Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared to the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplemental materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.
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.
Blind deconvolution using an improved L0 sparse representation
NASA Astrophysics Data System (ADS)
Ye, Pengzhao; Feng, Huajun; Li, Qi; Xu, Zhihai; Chen, Yueting
2014-09-01
In this paper, we present a method for single image blind deconvolution. Many common forms of blind deconvolution methods need to previously generate a salient image, while the paper presents a novel L0 sparse expression to directly solve the ill-positioned problem. It has no need to filter the blurred image as a restoration step and can use the gradient information as a fidelity term during optimization. The key to blind deconvolution problem is to estimate an accurate kernel. First, based on L2 sparse expression using gradient operator as a prior, the kernel can be estimated roughly and efficiently in the frequency domain. We adopt the multi-scale scheme which can estimate blur kernel from coarser level to finer level. After the estimation of this level's kernel, L0 sparse representation is employed as the fidelity term during restoration. After derivation, L0 norm can be approximately converted to a sum term and L1 norm term which can be addressed by the Split-Bregman method. By using the estimated blur kernel and the TV deconvolution model, the final restoration image is obtained. Experimental results show that the proposed method is fast and can accurately reconstruct the kernel, especially when the blur is motion blur, defocus blur or the superposition of the two. The restored image is of higher quality than that of some of the art algorithms.
1982-10-27
sparse matrices as well as other areas. Contents 1. operations on Sparse Matrices .. . . . . . . . . . . . . . . . . . . . . . . . I 1.1 Multi...22 2.1.1 Nonsymmetric systems ............................................. 22 2.1.1.1 General sparse matrices ...46 2.1.2.1 General sparse matrices ......................................... 46 2.1.2.2 Band or profile forms
Structured sparse models for classification
NASA Astrophysics Data System (ADS)
Castrodad, Alexey
The main focus of this thesis is the modeling and classification of high dimensional data using structured sparsity. Sparse models, where data is assumed to be well represented as a linear combination of a few elements from a dictionary, have gained considerable attention in recent years, and its use has led to state-of-the-art results in many signal and image processing tasks. The success of sparse modeling is highly due to its ability to efficiently use the redundancy of the data and find its underlying structure. On a classification setting, we capitalize on this advantage to properly model and separate the structure of the classes. We design and validate modeling solutions to challenging problems arising in computer vision and remote sensing. We propose both supervised and unsupervised schemes for the modeling of human actions from motion imagery under a wide variety of acquisition condi- tions. In the supervised case, the main goal is to classify the human actions in the video given a predefined set of actions to learn from. In the unsupervised case, the main goal is to an- alyze the spatio-temporal dynamics of the individuals in the scene without having any prior information on the actions themselves. We also propose a model for remotely sensed hysper- spectral imagery, where the main goal is to perform automatic spectral source separation and mapping at the subpixel level. Finally, we present a sparse model for sensor fusion to exploit the common structure and enforce collaboration of hyperspectral with LiDAR data for better mapping capabilities. In all these scenarios, we demonstrate that these data can be expressed as a combination of atoms from a class-structured dictionary. These data representation becomes essentially a "mixture of classes," and by directly exploiting the sparse codes, one can attain highly accurate classification performance with relatively unsophisticated classifiers.
Double shrinking sparse dimension reduction.
Zhou, Tianyi; Tao, Dacheng
2013-01-01
Learning tasks such as classification and clustering usually perform better and cost less (time and space) on compressed representations than on the original data. Previous works mainly compress data via dimension reduction. In this paper, we propose "double shrinking" to compress image data on both dimensionality and cardinality via building either sparse low-dimensional representations or a sparse projection matrix for dimension reduction. We formulate a double shrinking model (DSM) as an l(1) regularized variance maximization with constraint ||x||(2)=1, and develop a double shrinking algorithm (DSA) to optimize DSM. DSA is a path-following algorithm that can build the whole solution path of locally optimal solutions of different sparse levels. Each solution on the path is a "warm start" for searching the next sparser one. In each iteration of DSA, the direction, the step size, and the Lagrangian multiplier are deduced from the Karush-Kuhn-Tucker conditions. The magnitudes of trivial variables are shrunk and the importances of critical variables are simultaneously augmented along the selected direction with the determined step length. Double shrinking can be applied to manifold learning and feature selections for better interpretation of features, and can be combined with classification and clustering to boost their performance. The experimental results suggest that double shrinking produces efficient and effective data compression.
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.
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.
NASA Technical Reports Server (NTRS)
Vranish, John M. (Inventor)
1993-01-01
A split spline screw type payload fastener assembly, including three identical male and female type split spline sections, is discussed. The male spline sections are formed on the head of a male type spline driver. Each of the split male type spline sections has an outwardly projecting load baring segment including a convex upper surface which is adapted to engage a complementary concave surface of a female spline receptor in the form of a hollow bolt head. Additionally, the male spline section also includes a horizontal spline releasing segment and a spline tightening segment below each load bearing segment. The spline tightening segment consists of a vertical web of constant thickness. The web has at least one flat vertical wall surface which is designed to contact a generally flat vertically extending wall surface tab of the bolt head. Mutual interlocking and unlocking of the male and female splines results upon clockwise and counter clockwise turning of the driver element.
Successive splitting of autowaves in a nonlinear chemical reaction medium.
Okano, Taiji; Matsuda, Yuki; Miyakawa, Kenji
2006-12-01
The phenomenon of wave splitting is investigated in a two-dimensional excitable light-sensitive Belousov-Zhabotinsky reaction medium after extremely changing the intensity of illuminated light for a short time. It is found that successive wave splitting and nonannihilation collision between two waves of different amplitudes occur spontaneously under narrow experimental conditions. Experimental observations are approximately reproduced in the specific parameter range by a numerical simulation with a Bär-Eiswirth model.
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.
Ren, Lu; Jin, Lei; Wang, Jian-Bo; Yang, Fan; Qiu, Ming-Qiang; Yu, Ying
2009-03-18
Monoclinic structured BiVO(4) nanotubes have been selectively prepared by a template-free and surfactant-free solvothermal process in an ethanol-H(2)O mixed solvent. Interestingly, the nanotubes obtained at V(ethanol):V(water) = 3:1 have hexagonal cross sections with long lengths of approx. 1.2 microm, side lengths of approx. 200 nm and wall thicknesses of approx. 30 nm. A possible oriented attachment growth mechanism has been proposed based on the results of time-dependent experiments. Nanoplates were firstly formed by aggregation of primary nanocrystallites and then self-assembly converted to hexagonal-prismatic nanotubes via the corresponding oriented attachment mechanism. During this process, the presence of ethanol and the volume ratio of ethanol and water play important roles in the formation of the nanotubes with hexagonal cross sections. UV-vis spectroscopy was further employed to estimate the bandgap energy of the novel structure, which is larger (2.53 eV) than that for the bulk BiVO(4). The valence band edge position for the as-synthesized material was estimated to be 2.8 eV, which is positive enough for water oxidation. The photocatalytic activity for O(2) evolution from water splitting over the samples under visible light (lambda>420 nm) irradiation was investigated by using AgNO(3) as a sacrificial reagent. Experiment results indicate that the as-synthesized nanotubes exhibit higher photocatalytic activities for O(2) evolution than that of bulk BiVO(4), which is attributed to the special tubular structure morphology.
Sparse recovery via convex optimization
NASA Astrophysics Data System (ADS)
Randall, Paige Alicia
This thesis considers the problem of estimating a sparse signal from a few (possibly noisy) linear measurements. In other words, we have y = Ax + z where A is a measurement matrix with more columns than rows, x is a sparse signal to be estimated, z is a noise vector, and y is a vector of measurements. This setup arises frequently in many problems ranging from MRI imaging to genomics to compressed sensing.We begin by relating our setup to an error correction problem over the reals, where a received encoded message is corrupted by a few arbitrary errors, as well as smaller dense errors. We show that under suitable conditions on the encoding matrix and on the number of arbitrary errors, one is able to accurately recover the message.We next show that we are able to achieve oracle optimality for x, up to a log factor and a factor of sqrt{s}, when we require the matrix A to obey an incoherence property. The incoherence property is novel in that it allows the coherence of A to be as large as O(1/ log n) and still allows sparsities as large as O(m/log n). This is in contrast to other existing results involving coherence where the coherence can only be as large as O(1/sqrt{m}) to allow sparsities as large as O(sqrt{m}). We also do not make the common assumption that the matrix A obeys a restricted eigenvalue condition.We then show that we can recover a (non-sparse) signal from a few linear measurements when the signal has an exactly sparse representation in an overcomplete dictionary. We again only require that the dictionary obey an incoherence property.Finally, we introduce the method of l_1 analysis and show that it is guaranteed to give good recovery of a signal from a few measurements, when the signal can be well represented in a dictionary. We require that the combined measurement/dictionary matrix satisfies a uniform uncertainty principle and we compare our results with the more standard l_1 synthesis approach.All our methods involve solving an l_1 minimization
Splitting of asphaltene species
Galimov, R.A.; Yusupova, T.N.; Abushaeva, V.V.
1994-05-10
The extent of splitting of asphaltene species under the action of solvents correlates with their nature, and primarily with their electron- and proton-donor properties. According to the data of thermal analysis asphaltene species being retained after the action of solvents differ in the weight ratio of peripheral substituents to condensed part and in the fraction of labile bonds. 12 refs., 4 tabs.
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.
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.
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…
ERIC Educational Resources Information Center
Roberson, Kelly
1997-01-01
Presents photographs and the floor plan of a middle school whose split-level design separates "noisy" areas, such as the band room and gymnasium, from the academic wing. The design encourages teaming and flexibility through its classroom clustering and mobile partitions between classrooms. Additionally, all classrooms possess windows and…
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…
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.
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 Coding for Alpha Matting.
Johnson, Jubin; Varnousfaderani, Ehsan Shahrian; Cholakkal, Hisham; Rajan, Deepu
2016-07-01
Existing color sampling-based alpha matting methods use the compositing equation to estimate alpha at a pixel from the pairs of foreground ( F ) and background ( B ) samples. The quality of the matte depends on the selected ( F,B ) pairs. In this paper, the matting problem is reinterpreted as a sparse coding of pixel features, wherein the sum of the codes gives the estimate of the alpha matte from a set of unpaired F and B samples. A non-parametric probabilistic segmentation provides a certainty measure on the pixel belonging to foreground or background, based on which a dictionary is formed for use in sparse coding. By removing the restriction to conform to ( F,B ) pairs, this method allows for better alpha estimation from multiple F and B samples. The same framework is extended to videos, where the requirement of temporal coherence is handled effectively. Here, the dictionary is formed by samples from multiple frames. A multi-frame graph model, as opposed to a single image as for image matting, is proposed that can be solved efficiently in closed form. Quantitative and qualitative evaluations on a benchmark dataset are provided to show that the proposed method outperforms the current stateoftheart in image and video matting.
Sparse Coding for Alpha Matting.
Johnson, Jubin; Varnousfaderani, Ehsan; Cholakkal, Hisham; Rajan, Deepu
2016-04-21
Existing color sampling based alpha matting methods use the compositing equation to estimate alpha at a pixel from pairs of foreground (F) and background (B) samples. The quality of the matte depends on the selected (F,B) pairs. In this paper, the matting problem is reinterpreted as a sparse coding of pixel features, wherein the sum of the codes gives the estimate of the alpha matte from a set of unpaired F and B samples. A non-parametric probabilistic segmentation provides a certainty measure on the pixel belonging to foreground or background, based on which a dictionary is formed for use in sparse coding. By removing the restriction to conform to (F,B) pairs, this method allows for better alpha estimation from multiple F and B samples. The same framework is extended to videos, where the requirement of temporal coherence is handled effectively. Here, the dictionary is formed by samples from multiple frames. A multi-frame graph model, as opposed to a single image as for image matting, is proposed that can be solved efficiently in closed form. Quantitative and qualitative evaluations on a benchmark dataset are provided to show that the proposed method outperforms current state-of-the-art in image and video matting.
Universal Priors for Sparse Modeling(PREPRINT)
2009-08-01
UNIVERSAL PRIORS FOR SPARSE MODELING By Ignacio Ramı́rez Federico Lecumberry and Guillermo Sapiro IMA Preprint Series # 2276 ( August 2009...8-98) Prescribed by ANSI Std Z39-18 Universal Priors for Sparse Modeling (Invited Paper) Ignacio Ramı́rez#1, Federico Lecumberry ∗2, Guillermo Sapiro...I. Ramirez, F. Lecumberry , and G. Sapiro. Sparse modeling with univer- sal priors and learned incoherent dictionaries. Submitted to NIPS, 2009. [22
Discriminative Sparse Representations in Hyperspectral Imagery
2010-03-01
classification , and unsupervised labeling (clustering) [2, 3, 4, 5, 6, 7, 8]. Recently, a non-parametric (Bayesian) approach to sparse modeling and com...DISCRIMINATIVE SPARSE REPRESENTATIONS IN HYPERSPECTRAL IMAGERY By Alexey Castrodad, Zhengming Xing John Greer, Edward Bosch Lawrence Carin and...00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Discriminative Sparse Representations in Hyperspectral Imagery 5a. CONTRACT NUMBER 5b. GRANT
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.
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.
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.
Fee splitting in ophthalmology.
Levin, Alex V; Ganesh, Anuradha; Al-Busaidi, Ahmed
2011-02-01
Fee splitting and co-management are common practices in ophthalmology. These arrangements may conflict with the ethical principles governing the doctor-patient relationship, may constitute professional misconduct, and at times, may be illegal. Implications and perceptions of these practices may vary between different cultures. Full disclosure to the patient may minimize the adverse effects of conflicts of interest that arise from these practices, and may thereby allow these practices to be deemed acceptable by some cultural morays, professional guidelines, or by law. Disclosure does not necessarily relieve the physician from a potential ethical compromise. This review examines the practice of fee splitting in ophthalmology, its legal implications, the policies or guidelines governing such arrangements, and the possible ethical ramifications. A comparative view between 3 countries, Canada, the United States, and Oman, was conducted; illustrating that even in disparate cultures, there may be some universality to the application of ethical principles.
Split Bregman's optimization method for image construction in compressive sensing
NASA Astrophysics Data System (ADS)
Skinner, D.; Foo, S.; Meyer-Bäse, A.
2014-05-01
The theory of compressive sampling (CS) was reintroduced by Candes, Romberg and Tao, and D. Donoho in 2006. Using a priori knowledge that a signal is sparse, it has been mathematically proven that CS can defY Nyquist sampling theorem. Theoretically, reconstruction of a CS image relies on the minimization and optimization techniques to solve this complex almost NP-complete problem. There are many paths to consider when compressing and reconstructing an image but these methods have remained untested and unclear on natural images, such as underwater sonar images. The goal of this research is to perfectly reconstruct the original sonar image from a sparse signal while maintaining pertinent information, such as mine-like object, in Side-scan sonar (SSS) images. Goldstein and Osher have shown how to use an iterative method to reconstruct the original image through a method called Split Bregman's iteration. This method "decouples" the energies using portions of the energy from both the !1 and !2 norm. Once the energies are split, Bregman iteration is used to solve the unconstrained optimization problem by recursively solving the problems simultaneously. The faster these two steps or energies can be solved then the faster the overall method becomes. While the majority of CS research is still focused on the medical field, this paper will demonstrate the effectiveness of the Split Bregman's methods on sonar images.
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.
Sparse and stable Markowitz portfolios.
Brodie, Joshua; Daubechies, Ingrid; De Mol, Christine; Giannone, Domenico; Loris, Ignace
2009-07-28
We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio.
Approximate Orthogonal Sparse Embedding for Dimensionality Reduction.
Lai, Zhihui; Wong, Wai Keung; Xu, Yong; Yang, Jian; Zhang, David
2016-04-01
Locally linear embedding (LLE) is one of the most well-known manifold learning methods. As the representative linear extension of LLE, orthogonal neighborhood preserving projection (ONPP) has attracted widespread attention in the field of dimensionality reduction. In this paper, a unified sparse learning framework is proposed by introducing the sparsity or L1-norm learning, which further extends the LLE-based methods to sparse cases. Theoretical connections between the ONPP and the proposed sparse linear embedding are discovered. The optimal sparse embeddings derived from the proposed framework can be computed by iterating the modified elastic net and singular value decomposition. We also show that the proposed model can be viewed as a general model for sparse linear and nonlinear (kernel) subspace learning. Based on this general model, sparse kernel embedding is also proposed for nonlinear sparse feature extraction. Extensive experiments on five databases demonstrate that the proposed sparse learning framework performs better than the existing subspace learning algorithm, particularly in the cases of small sample sizes.
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.
Segmented holographic spectrum splitting concentrator
NASA Astrophysics Data System (ADS)
Ayala, Silvana P.; Vorndran, Shelby; Wu, Yuechen; Chrysler, Benjamin; Kostuk, Raymond K.
2016-09-01
This paper presents a segmented parabolic concentrator employing holographic spectral filters that provide focusing and spectral bandwidth separation capability to the system. Strips of low band gap silicon photovoltaic (PV) cells are formed into a parabolic surface as shown by Holman et. al. [1]. The surface of the PV segments is covered with holographic elements formed in dichromated gelatin. The holographic elements are designed to transmit longer wavelengths to silicon cells, and to reflect short wavelength light towards a secondary collector where high-bandgap PV cells are mounted. The system can be optimized for different combinations of diffuse and direct solar illumination conditions for particular geographical locations by controlling the concentration ratio and filtering properties of the holographic elements. In addition, the reflectivity of the back contact of the silicon cells is used to increase the optical path length and light trapping. This potentially allows the use of thin film silicon for the low bandgap PV cell material. The optical design combines the focusing properties of the parabolic concentrator and the holographic element to control the concentration ratio and uniformity of the spectral distribution at the high bandgap cell location. The presentation concludes with a comparison of different spectrum splitting holographic filter materials for this application.
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.
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.
NASA Astrophysics Data System (ADS)
Bazeia, D.; Losano, L.; Marques, M. A.; Menezes, R.
2017-02-01
We investigate the presence of non-topological solutions of the Q-ball type in (1 , 1) spacetime dimensions. The model engenders the global U (1) symmetry and is of the k-field type, since it contains a new term, of the fourth-order power in the derivative of the complex scalar field. It supports analytical solution of the Q-ball type which is stable quantum mechanically. The new solution engenders an interesting behavior, with the charge and energy densities unveiling a splitting profile.
Fast estimation of sparse doubly spread acoustic channels.
Zeng, Wen-Jun; Xu, Wen
2012-01-01
The estimation of doubly spread underwater acoustic channels is addressed. By exploiting the sparsity in the delay-Doppler domain, this paper proposes a fast projected gradient method (FPGM) that can handle complex-valued data for estimating the delay-Doppler spread function of a time-varying channel. The proposed FPGM formulates the sparse channel estimation as a complex-valued convex optimization using an [script-l](1)-norm constraint. Conventional approaches to complex-valued optimization split the complex variables into their real and imaginary parts; this doubles the dimension compared with the original problem and may break the special data structure. Unlike the conventional methods, the proposed method directly handles the complex variables as a whole without splitting them into real numbers; hence the dimension will not increase. By exploiting the block Toeplitz-like structure of the coefficient matrix, the computational complexity of the FPGM is reduced to O(LNlogN), where L is the dimension of the Doppler shift and N is the signal length. Simulation results verify the accuracy and efficiency of the FPGM, indicating that is robust to parameter selection and is orders-of-magnitude faster than standard convex optimization algorithms. The Kauai experimental data processing results are also provided to demonstrate the performance of the proposed algorithm.
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.
Sparse-aperture adaptive optics
NASA Astrophysics Data System (ADS)
Tuthill, Peter; Lloyd, James; Ireland, Michael; Martinache, Frantz; Monnier, John; Woodruff, Henry; ten Brummelaar, Theo; Turner, Nils; Townes, Charles
2006-06-01
Aperture masking interferometry and Adaptive Optics (AO) are two of the competing technologies attempting to recover diffraction-limited performance from ground-based telescopes. However, there are good arguments that these techniques should be viewed as complementary, not competitive. Masking has been shown to deliver superior PSF calibration, rejection of atmospheric noise and robust recovery of phase information through the use of closure phases. However, this comes at the penalty of loss of flux at the mask, restricting the technique to bright targets. Adaptive optics, on the other hand, can reach a fainter class of objects but suffers from the difficulty of calibration of the PSF which can vary with observational parameters such as seeing, airmass and source brightness. Here we present results from a fusion of these two techniques: placing an aperture mask downstream of an AO system. The precision characterization of the PSF enabled by sparse-aperture interferometry can now be applied to deconvolution of AO images, recovering structure from the traditionally-difficult regime within the core of the AO-corrected transfer function. Results of this program from the Palomar and Keck adaptive optical systems are presented.
Resistant multiple sparse canonical correlation.
Coleman, Jacob; Replogle, Joseph; Chandler, Gabriel; Hardin, Johanna
2016-04-01
Canonical correlation analysis (CCA) is a multivariate technique that takes two datasets and forms the most highly correlated possible pairs of linear combinations between them. Each subsequent pair of linear combinations is orthogonal to the preceding pair, meaning that new information is gleaned from each pair. By looking at the magnitude of coefficient values, we can find out which variables can be grouped together, thus better understanding multiple interactions that are otherwise difficult to compute or grasp intuitively. CCA appears to have quite powerful applications to high-throughput data, as we can use it to discover, for example, relationships between gene expression and gene copy number variation. One of the biggest problems of CCA is that the number of variables (often upwards of 10,000) makes biological interpretation of linear combinations nearly impossible. To limit variable output, we have employed a method known as sparse canonical correlation analysis (SCCA), while adding estimation which is resistant to extreme observations or other types of deviant data. In this paper, we have demonstrated the success of resistant estimation in variable selection using SCCA. Additionally, we have used SCCA to find multiple canonical pairs for extended knowledge about the datasets at hand. Again, using resistant estimators provided more accurate estimates than standard estimators in the multiple canonical correlation setting. R code is available and documented at https://github.com/hardin47/rmscca.
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
Robust compressive sensing of sparse signals: a review
NASA Astrophysics Data System (ADS)
Carrillo, Rafael E.; Ramirez, Ana B.; Arce, Gonzalo R.; Barner, Kenneth E.; Sadler, Brian M.
2016-12-01
Compressive sensing generally relies on the ℓ 2 norm for data fidelity, whereas in many applications, robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the presence of impulsive noise, i.e., measurements are corrupted by outliers, are of particular importance. This article overviews robust nonlinear reconstruction strategies for sparse signals based on replacing the commonly used ℓ 2 norm by M-estimators as data fidelity functions. The derived methods outperform existing compressed sensing techniques in impulsive environments, while achieving good performance in light-tailed environments, thus offering a robust framework for CS.
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.
Structured sparse priors for image classification.
Srinivas, Umamahesh; Suo, Yuanming; Dao, Minh; Monga, Vishal; Tran, Trac D
2015-06-01
Model-based compressive sensing (CS) exploits the structure inherent in sparse signals for the design of better signal recovery algorithms. This information about structure is often captured in the form of a prior on the sparse coefficients, with the Laplacian being the most common such choice (leading to l1 -norm minimization). Recent work has exploited the discriminative capability of sparse representations for image classification by employing class-specific dictionaries in the CS framework. Our contribution is a logical extension of these ideas into structured sparsity for classification. We introduce the notion of discriminative class-specific priors in conjunction with class specific dictionaries, specifically the spike-and-slab prior widely applied in Bayesian sparse regression. Significantly, the proposed framework takes the burden off the demand for abundant training image samples necessary for the success of sparsity-based classification schemes. We demonstrate this practical benefit of our approach in important applications, such as face recognition and object categorization.
Robust feature point matching with sparse model.
Jiang, Bo; Tang, Jin; Luo, Bin; Lin, Liang
2014-12-01
Feature point matching that incorporates pairwise constraints can be cast as an integer quadratic programming (IQP) problem. Since it is NP-hard, approximate methods are required. The optimal solution for IQP matching problem is discrete, binary, and thus sparse in nature. This motivates us to use sparse model for feature point matching problem. The main advantage of the proposed sparse feature point matching (SPM) method is that it generates sparse solution and thus naturally imposes the discrete mapping constraints approximately in the optimization process. Therefore, it can optimize the IQP matching problem in an approximate discrete domain. In addition, an efficient algorithm can be derived to solve SPM problem. Promising experimental results on both synthetic points sets matching and real-world image feature sets matching tasks show the effectiveness of the proposed feature point matching method.
Online Dictionary Learning for Sparse Coding
2009-04-01
cessing tasks such as denoising (Elad & Aharon, 2006) as well as higher-level tasks such as classification (Raina et al., 2007; Mairal et al., 2008a...Bruckstein, A. M. (2006). The K- SVD : An algorithm for designing of overcomplete dic- tionaries for sparse representations. IEEE Trans. SP...Tibshirani, R. (2004). Least angle regression. Ann. Statist. Elad, M., & Aharon, M. (2006). Image denoising via sparse and redundant representations
Sparse CSEM inversion driven by seismic coherence
NASA Astrophysics Data System (ADS)
Guo, Zhenwei; Dong, Hefeng; Kristensen, Åge
2016-12-01
Marine controlled source electromagnetic (CSEM) data inversion for hydrocarbon exploration is often challenging due to high computational cost, physical memory requirement and low resolution of the obtained resistivity map. This paper aims to enhance both the speed and resolution of CSEM inversion by introducing structural geological information in the inversion algorithm. A coarse mesh is generated for Occam’s inversion, where the parameters are fewer than in the fine regular mesh. This sparse mesh is defined as a coherence-based irregular (IC) sparse mesh, which is based on vertices extracted from available geological information. Inversion results on synthetic data illustrate that the IC sparse mesh has a smaller inversion computational cost compared to the regular dense (RD) mesh. It also has a higher resolution than with a regular sparse (RS) mesh for the same number of estimated parameters. In order to study how the IC sparse mesh reduces the computational time, four different meshes are generated for Occam’s inversion. As a result, an IC sparse mesh can reduce the computational cost while it keeps the resolution as good as a fine regular mesh. The IC sparse mesh reduces the computational cost of the matrix operation for model updates. When the number of estimated parameters reduces to a limited value, the computational cost is independent of the number of parameters. For a testing model with two resistive layers, the inversion result using an IC sparse mesh has higher resolution in both horizontal and vertical directions. Overall, the model representing significant geological information in the IC mesh can improve the resolution of the resistivity models obtained from inversion of CSEM data.
Sparse Extreme Learning Machine for Classification
Bai, Zuo; Huang, Guang-Bin; Wang, Danwei; Wang, Han; Westover, M. Brandon
2016-01-01
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.
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.
Efficient, sparse biological network determination
August, Elias; Papachristodoulou, Antonis
2009-01-01
Background Determining the interaction topology of biological systems is a topic that currently attracts significant research interest. Typical models for such systems take the form of differential equations that involve polynomial and rational functions. Such nonlinear models make the problem of determining the connectivity of biochemical networks from time-series experimental data much harder. The use of linear dynamics and linearization techniques that have been proposed in the past can circumvent this, but the general problem of developing efficient algorithms for models that provide more accurate system descriptions remains open. Results We present a network determination algorithm that can treat model descriptions with polynomial and rational functions and which does not make use of linearization. For this purpose, we make use of the observation that biochemical networks are in general 'sparse' and minimize the 1-norm of the decision variables (sum of weighted network connections) while constraints keep the error between data and the network dynamics small. The emphasis of our methodology is on determining the interconnection topology rather than the specific reaction constants and it takes into account the necessary properties that a chemical reaction network should have – something that techniques based on linearization can not. The problem can be formulated as a Linear Program, a convex optimization problem, for which efficient algorithms are available that can treat large data sets efficiently and uncertainties in data or model parameters. Conclusion The presented methodology is able to predict with accuracy and efficiency the connectivity structure of a chemical reaction network with mass action kinetics and of a gene regulatory network from simulation data even if the dynamics of these systems are non-polynomial (rational) and uncertainties in the data are taken into account. It also produces a network structure that can explain the real experimental
NASA Technical Reports Server (NTRS)
Liou, Meng-Sing; Steffen, Christopher J., Jr.
1991-01-01
A new flux splitting scheme is proposed. The scheme is remarkably simple and yet its accuracy rivals and in some cases surpasses that of Roe's solver in the Euler and Navier-Stokes solutions performed in this study. The scheme is robust and converges as fast as the Roe splitting. An approximately defined cell-face advection Mach number is proposed using values from the two straddling cells via associated characteristic speeds. This interface Mach number is then used to determine the upwind extrapolation for the convective quantities. Accordingly, the name of the scheme is coined as Advection Upstream Splitting Method (AUSM). A new pressure splitting is introduced which is shown to behave successfully, yielding much smoother results than other existing pressure splittings. Of particular interest is the supersonic blunt body problem in which the Roe scheme gives anomalous solutions. The AUSM produces correct solutions without difficulty for a wide range of flow conditions as well as grids.
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.
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.
Resonant Nanophotonic Spectrum Splitting for Ultrathin Multijunction Solar Cells.
Mann, Sander A; Garnett, Erik C
2015-07-15
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.
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
Split-sideband spectroscopy in slowly modulated optomechanics
NASA Astrophysics Data System (ADS)
Aranas, E. B.; Fonseca, P. Z. G.; Barker, P. F.; Monteiro, T. S.
2016-11-01
Optomechanical coupling between the motion of a mechanical oscillator and a cavity represents a new arena for experimental investigation of quantum effects on the mesoscopic and macroscopic scale. The motional sidebands of the output of a cavity offer ultra-sensitive probes of the dynamics. We introduce a scheme whereby these sidebands split asymmetrically and show how they may be used as experimental diagnostics and signatures of quantum noise limited dynamics. We show split-sidebands with controllable asymmetry occur by simultaneously modulating the light-mechanical coupling g and the mechanical frequency, {ω }{{M}}—slowly and out-of-phase. Such modulations are generic but already occur in optically trapped set-ups where the equilibrium point of the oscillator is varied cyclically. We analyse recently observed, but overlooked, experimental split-sideband asymmetries; although not yet in the quantum regime, the data suggests that split sideband structures are easily accessible to future experiments.
Chen, Shuhang; Liu, Huafeng; Hu, Zhenghui; Zhang, Heye; Shi, Pengcheng; Chen, Yunmei
2015-07-01
Although of great clinical value, accurate and robust reconstruction and segmentation of dynamic positron emission tomography (PET) images are great challenges due to low spatial resolution and high noise. In this paper, we propose a unified framework that exploits temporal correlations and variations within image sequences based on low-rank and sparse matrix decomposition. Thus, the two separate inverse problems, PET image reconstruction and segmentation, are accomplished in a simultaneous fashion. Considering low signal to noise ratio and piece-wise constant assumption of PET images, we also propose to regularize low-rank and sparse matrices with vectorial total variation norm. The resulting optimization problem is solved by augmented Lagrangian multiplier method with variable splitting. The effectiveness of proposed approach is validated on realistic Monte Carlo simulation datasets and the real patient data.
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.
Non-split and split deformations of {{AdS}}_{5}
NASA Astrophysics Data System (ADS)
Hoare, Ben; van Tongeren, Stijn J.
2016-12-01
The η deformation of the {{AdS}}5× {S}5 superstring depends on a non-split r matrix for the superalgebra {psu}(2,2| 4). Much of the investigation into this model has considered one particular choice, however there are a number of inequivalent alternatives. This is also true for the bosonic sector of the theory with {su}(2,2), the isometry algebra of {{AdS}}5, admitting one split and three non-split r matrices. In this article we explore these r matrices and the corresponding geometries. We investigate their contraction limits, comment on supergravity backgrounds and demonstrate their relation to gauged-WZW deformations. We then extend the three non-split cases to {{AdS}}5× {S}5 and compute four separate bosonic two-particle tree-level S-matrices based on inequivalent BMN-type light-cone gauges. The resulting S-matrices, while different, are related by momentum-dependent one-particle changes of basis.
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
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.
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.
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.
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.
A unified approach to sparse signal processing
NASA Astrophysics Data System (ADS)
Marvasti, Farokh; Amini, Arash; Haddadi, Farzan; Soltanolkotabi, Mahdi; Khalaj, Babak Hossein; Aldroubi, Akram; Sanei, Saeid; Chambers, Janathon
2012-12-01
A unified view of the area of sparse signal processing is presented in tutorial form by bringing together various fields in which the property of sparsity has been successfully exploited. For each of these fields, various algorithms and techniques, which have been developed to leverage sparsity, are described succinctly. The common potential benefits of significant reduction in sampling rate and processing manipulations through sparse signal processing are revealed. The key application domains of sparse signal processing are sampling, coding, spectral estimation, array processing, component analysis, and multipath channel estimation. In terms of the sampling process and reconstruction algorithms, linkages are made with random sampling, compressed sensing, and rate of innovation. The redundancy introduced by channel coding in finite and real Galois fields is then related to over-sampling with similar reconstruction algorithms. The error locator polynomial (ELP) and iterative methods are shown to work quite effectively for both sampling and coding applications. The methods of Prony, Pisarenko, and MUltiple SIgnal Classification (MUSIC) are next shown to be targeted at analyzing signals with sparse frequency domain representations. Specifically, the relations of the approach of Prony to an annihilating filter in rate of innovation and ELP in coding are emphasized; the Pisarenko and MUSIC methods are further improvements of the Prony method under noisy environments. The iterative methods developed for sampling and coding applications are shown to be powerful tools in spectral estimation. Such narrowband spectral estimation is then related to multi-source location and direction of arrival estimation in array processing. Sparsity in unobservable source signals is also shown to facilitate source separation in sparse component analysis; the algorithms developed in this area such as linear programming and matching pursuit are also widely used in compressed sensing. Finally
Protein family classification using sparse Markov transducers.
Eskin, E; Grundy, W N; Singer, Y
2000-01-01
In this paper we present a method for classifying proteins into families using sparse Markov transducers (SMTs). Sparse Markov transducers, similar to probabilistic suffix trees, estimate a probability distribution conditioned on an input sequence. SMTs generalize probabilistic suffix trees by allowing for wild-cards in the conditioning sequences. Because substitutions of amino acids are common in protein families, incorporating wildcards into the model significantly improves classification performance. We present two models for building protein family classifiers using SMTs. We also present efficient data structures to improve the memory usage of the models. We evaluate SMTs by building protein family classifiers using the Pfam database and compare our results to previously published results.
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.
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.
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.
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
Structured Sparse Method for Hyperspectral Unmixing
NASA Astrophysics Data System (ADS)
Zhu, Feiyun; Wang, Ying; Xiang, Shiming; Fan, Bin; Pan, Chunhong
2014-02-01
Hyperspectral Unmixing (HU) has received increasing attention in the past decades due to its ability of unveiling information latent in hyperspectral data. Unfortunately, most existing methods fail to take advantage of the spatial information in data. To overcome this limitation, we propose a Structured Sparse regularized Nonnegative Matrix Factorization (SS-NMF) method based on the following two aspects. First, we incorporate a graph Laplacian to encode the manifold structures embedded in the hyperspectral data space. In this way, the highly similar neighboring pixels can be grouped together. Second, the lasso penalty is employed in SS-NMF for the fact that pixels in the same manifold structure are sparsely mixed by a common set of relevant bases. These two factors act as a new structured sparse constraint. With this constraint, our method can learn a compact space, where highly similar pixels are grouped to share correlated sparse representations. Experiments on real hyperspectral data sets with different noise levels demonstrate that our method outperforms the state-of-the-art methods significantly.
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.
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.
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.
Maxdenominator Reweighted Sparse Representation for Tumor Classification
Li, Weibiao; Liao, Bo; Zhu, Wen; Chen, Min; Peng, Li; Wei, Xiaohui; Gu, Changlong; Li, Keqin
2017-01-01
The classification of tumors is crucial for the proper treatment of cancer. Sparse representation-based classifier (SRC) exhibits good classification performance and has been successfully used to classify tumors using gene expression profile data. In this study, we propose a three-step maxdenominator reweighted sparse representation classification (MRSRC) method to classify tumors. First, we extract a set of metagenes from the training samples. These metagenes can capture the structures inherent to the data and are more effective for classification than the original gene expression data. Second, we use a reweighted regularization method to obtain the sparse representation coefficients. Reweighted regularization can enhance sparsity and obtain better sparse representation coefficients. Third, we classify the data by utilizing a maxdenominator residual error function. Maxdenominator strategy can reduce the residual error and improve the accuracy of the final classification. Extensive experiments using publicly available gene expression profile data sets show that the performance of MRSRC is comparable with or better than many existing representative methods. PMID:28393883
NASA Astrophysics Data System (ADS)
Lee, J. S.; Orlov, D. M.; Moyer, R. A.; Bykov, I.; Evans, T. E.; Wu, W.; Lyons, B. C.; Sugiyama, L. E.
2016-10-01
Magnetic field perturbations (RMPs) split the strike points in divertor tokamaks. This splitting is measured using fast imaging of filtered visible light from the divertor. We compare the observed splitting during n=3 RMP experiments to vacuum and plasma response modeling to determine if the measured splitting provides a sensitive diagnostic for the plasma response to the RMP. We also investigate the sensitivity of the computed plasma response to uncertainties in the initial 2D equilibrium. Strike point splitting was also observed in ELMing H-mode without the RMP, possibly due to n=1 error- and error-field correction fields. We compare the measured splitting during ELMs to linear plasma response modeling of the divertor footprints, and to nonlinear M3D ELM simulations. Work supported by U.S. DOE under Grant Numbers DE-FG02-07ER54917, DE-FG02-05ER54809.
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.
Biphasic water splitting by osmocene
Ge, Peiyu; Todorova, Tanya K.; Patir, Imren Hatay; Olaya, Astrid J.; Vrubel, Heron; Mendez, Manuel; Hu, Xile; Corminboeuf, Clémence; Girault, Hubert H.
2012-01-01
The photochemical reactivity of osmocene in a biphasic water-organic solvent system has been investigated to probe its water splitting properties. The photoreduction of aqueous protons to hydrogen under anaerobic conditions induced by osmocene dissolved in 1,2-dichloroethane and the subsequent water splitting by the osmocenium metal-metal dimer formed during H2 production were studied by electrochemical methods, UV-visible spectrometry, gas chromatography, and nuclear magnetic resonance spectroscopy. Density functional theory computations were used to validate the reaction pathways. PMID:22665787
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.
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.
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.
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.
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.
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.
Feature selection using sparse Bayesian inference
NASA Astrophysics Data System (ADS)
Brandes, T. Scott; Baxter, James R.; Woodworth, Jonathan
2014-06-01
A process for selecting a sparse subset of features that maximize discrimination between target classes is described in a Bayesian framework. Demonstrated on high range resolution radar (HRR) signature data, this has the effect of selecting the most informative range bins for a classification task. The sparse Bayesian classifier (SBC) model is directly compared against Fisher's linear discriminant analysis (LDA), showing a clear performance gain with the Bayesian framework using HRRs from the publicly available MSTAR data set. The discriminative power of the selected features from the SBC is shown to be particularly dominant over LDA when only a few features are selected or when there is a shift in training and testing data sets, as demonstrated by training on a specific target type and testing on a slightly different target type.
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.
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.
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
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.
Hyperspectral Image Classification via Kernel Sparse Representation
2013-01-01
and sparse representations, image processing, wavelets, multirate systems , and filter banks . Nasser M. Nasrabadi (S’80–M’84–SM’92–F’01) received the...ery, sampling, multirate systems , filter banks , transforms, wavelets, and their applications in signal analysis, compression, processing, and...University of Pavia and the Center of Pavia images, are urban images acquired by the Reflective Optics System Imaging Spectrom- eter (ROSIS). The ROSIS
Sparse Representation for Time-Series Classification
2015-02-08
February 8, 2015 16:49 World Scientific Review Volume - 9in x 6in ” time - series classification” page 1 Chapter 1 Sparse Representation for Time - Series ...studies the problem of time - series classification and presents an overview of recent developments in the area of feature extraction and information...problem of target classification, and more generally time - series classification, in two main directions, feature extraction and information fusion. 1
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.
Sparseness- and continuity-constrained seismic imaging
NASA Astrophysics Data System (ADS)
Herrmann, Felix J.
2005-04-01
Non-linear solution strategies to the least-squares seismic inverse-scattering problem with sparseness and continuity constraints are proposed. Our approach is designed to (i) deal with substantial amounts of additive noise (SNR < 0 dB); (ii) use the sparseness and locality (both in position and angle) of directional basis functions (such as curvelets and contourlets) on the model: the reflectivity; and (iii) exploit the near invariance of these basis functions under the normal operator, i.e., the scattering-followed-by-imaging operator. Signal-to-noise ratio and the continuity along the imaged reflectors are significantly enhanced by formulating the solution of the seismic inverse problem in terms of an optimization problem. During the optimization, sparseness on the basis and continuity along the reflectors are imposed by jointly minimizing the l1- and anisotropic diffusion/total-variation norms on the coefficients and reflectivity, respectively. [Joint work with Peyman P. Moghaddam was carried out as part of the SINBAD project, with financial support secured through ITF (the Industry Technology Facilitator) from the following organizations: BG Group, BP, ExxonMobil, and SHELL. Additional funding came from the NSERC Discovery Grants 22R81254.
Imaging black holes with sparse modeling
NASA Astrophysics Data System (ADS)
Honma, Mareki; Akiyama, Kazunori; Tazaki, Fumie; Kuramochi, Kazuki; Ikeda, Shiro; Hada, Kazuhiro; Uemura, Makoto
2016-03-01
We introduce a new imaging method for radio interferometry based on sparse- modeling. The direct observables in radio interferometry are visibilities, which are Fourier transformation of an astronomical image on the sky-plane, and incomplete sampling of visibilities in the spatial frequency domain results in an under-determined problem, which has been usually solved with 0 filling to un-sampled grids. In this paper we propose to directly solve this under-determined problem using sparse modeling without 0 filling, which realizes super resolution, i.e., resolution higher than the standard refraction limit. We show simulation results of sparse modeling for the Event Horizon Telescope (EHT) observations of super-massive black holes and demonstrate that our approach has significant merit in observations of black hole shadows expected to be realized in near future. We also present some results with the method applied to real data, and also discuss more advanced techniques for practical observations such as imaging with closure phase as well as treating the effect of interstellar scattering effect.
Automatic target recognition via sparse representations
NASA Astrophysics Data System (ADS)
Estabridis, Katia
2010-04-01
Automatic target recognition (ATR) based on the emerging technology of Compressed Sensing (CS) can considerably improve accuracy, speed and cost associated with these types of systems. An image based ATR algorithm has been built upon this new theory, which can perform target detection and recognition in a low dimensional space. Compressed dictionaries (A) are formed to include rotational information for a scale of interest. The algorithm seeks to identify y(test sample) as a linear combination of the dictionary elements : y=Ax, where A ∈ Rnxm(n<
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.
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.
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.
Circadian regulation of cortisol release in behaviorally split golden hamsters.
Lilley, Travis R; Wotus, Cheryl; Taylor, Daniel; Lee, Jennifer M; de la Iglesia, Horacio O
2012-02-01
The master circadian clock located within the hypothalamic suprachiasmatic nucleus (SCN) is necessary for the circadian rhythm of glucocorticoid (GC) release. The pathways by which the SCN sustains rhythmic GC release remain unclear. We studied the circadian regulation of cortisol release in the behaviorally split golden hamster, in which the single bout of circadian locomotor activity splits into two bouts approximately 12 h apart after exposing the animals to constant light conditions. We show that unsplit control hamsters present a single peak of cortisol release that is concomitant with a single peak of ACTH release. In contrast, split hamsters show two peaks of cortisol release that are approximately 12 h appart and are appropriately phased to each locomotor activity bout but surprisingly do not rely on rhythmic release of ACTH. Our results are consistent with a model in which the circadian pacemaker within the SCN regulates the circadian release of GC via input to the hypothalamo-pituitary-adrenal axis and via a second regulatory pathway, which likely involves sympathetic innervation of the adrenal and can operate even in the absence of ACTH circadian rhythmic release. Furthermore, we show that although the overall 24-h cortisol output in split hamsters is lower than in unsplit controls, split hamsters release constant low levels of ACTH. This result suggests that the timing, rather than the absolute amount, of cortisol release is more critical for the induction of negative feedback effects that regulate the hypothalamo-pituitary-adrenal axis.
Grating beam splitting with liquid crystal adaptive optics
NASA Astrophysics Data System (ADS)
Albero, J.; Moreno, I.
2012-07-01
We report on the generation of equi-intense light beams from an adaptive point of view. A phase mask is generated and displayed onto a spatial light modulator, in order to divide an incoming light beam into a chosen number of beams. The use of liquid crystal spatial light modulators can introduce polarization into scalar designs as a parameter acting on the output efficiency. We reproduce the modulator optimal designs proposed theoretically in the literature and we add the polarization features. In addition, we compare this with another beam splitting technique, based on spatial multiplexing of phase masks. It spreads as low-level background noise the light concentrated on diffraction orders other than those targeted. We also demonstrate that using polarization with spatial light modulators can improve in some cases the optimal theoretical efficiencies. Experimental results agree with simulations.
Efficiency limits for photoelectrochemical water-splitting
Fountaine, Katherine T.; Lewerenz, Hans Joachim; Atwater, Harry A.
2016-01-01
Theoretical limiting efficiencies have a critical role in determining technological viability and expectations for device prototypes, as evidenced by the photovoltaics community's focus on detailed balance. However, due to their multicomponent nature, photoelectrochemical devices do not have an equivalent analogue to detailed balance, and reported theoretical efficiency limits vary depending on the assumptions made. Here we introduce a unified framework for photoelectrochemical device performance through which all previous limiting efficiencies can be understood and contextualized. Ideal and experimentally realistic limiting efficiencies are presented, and then generalized using five representative parameters—semiconductor absorption fraction, external radiative efficiency, series resistance, shunt resistance and catalytic exchange current density—to account for imperfect light absorption, charge transport and catalysis. Finally, we discuss the origin of deviations between the limits discussed herein and reported water-splitting efficiencies. This analysis provides insight into the primary factors that determine device performance and a powerful handle to improve device efficiency. PMID:27910847
Efficiency limits for photoelectrochemical water-splitting
NASA Astrophysics Data System (ADS)
Fountaine, Katherine T.; Lewerenz, Hans Joachim; Atwater, Harry A.
2016-12-01
Theoretical limiting efficiencies have a critical role in determining technological viability and expectations for device prototypes, as evidenced by the photovoltaics community's focus on detailed balance. However, due to their multicomponent nature, photoelectrochemical devices do not have an equivalent analogue to detailed balance, and reported theoretical efficiency limits vary depending on the assumptions made. Here we introduce a unified framework for photoelectrochemical device performance through which all previous limiting efficiencies can be understood and contextualized. Ideal and experimentally realistic limiting efficiencies are presented, and then generalized using five representative parameters--semiconductor absorption fraction, external radiative efficiency, series resistance, shunt resistance and catalytic exchange current density--to account for imperfect light absorption, charge transport and catalysis. Finally, we discuss the origin of deviations between the limits discussed herein and reported water-splitting efficiencies. This analysis provides insight into the primary factors that determine device performance and a powerful handle to improve device efficiency.
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.
Noor, Amina; Ahmad, Aitzaz; Serpedin, Erchin
2015-10-27
Network component analysis (NCA) is an important method for inferring transcriptional regulatory networks (TRNs) and recovering transcription factor activities (TFAs) using gene expression data, and the prior information about the connectivity matrix. The algorithms currently available crucially depend on the completeness of this prior information. However, inaccuracies in the measurement process may render incompleteness in the available knowledge about the connectivity matrix. Hence, computationally efficient algorithms are needed to overcome the possible incompleteness in the available data. We present a sparse network component analysis algorithm (sparseNCA), which incorporates the effect of incompleteness in the estimation of TRNs by imposing an additional sparsity constraint using the `1 norm, which results in a greater estimation accuracy. In order to improve the computational efficiency, an iterative re-weighted `2 method is proposed for the NCA problem which not only promotes sparsity but is hundreds of times faster than the `1 norm based solution. The performance of sparseNCA is rigorously compared to that of FastNCA and NINCA using synthetic data as well as real data. It is shown that sparseNCA outperforms the existing state-of-the-art algorithms both in terms of estimation accuracy and consistency with the added advantage of low computational complexity. The performance of sparseNCA compared to its predecessors is particularly pronounced in case of incomplete prior information about the sparsity of the network. Subnetwork analysis is performed on the E.coli data which reiterates the superior consistency of the proposed algorithm.
QIAN,S.TAKACS,P.
2003-08-03
A beam splitter to create two separated parallel beams is a critical unit of a pencil beam interferometer, for example the long trace profiler (LTP). The operating principle of the beam splitter can be based upon either amplitude-splitting (AS) or wavefront-splitting (WS). For precision measurements with the LTP, an equal optical path system with two parallel beams is desired. Frequency drift of the light source in a non-equal optical path system will cause the interference fringes to drift. An equal optical path prism beam splitter with an amplitude-splitting (AS-EBS) beam splitter and a phase shift beam splitter with a wavefront-splitting (WS-PSBS) are introduced. These beam splitters are well suited to the stability requirement for a pencil beam interferometer due to the characteristics of monolithic structure and equal optical path. Several techniques to produce WS-PSBS by hand are presented. In addition, the WS-PSBS using double thin plates, made from microscope cover plates, has great advantages of economy, convenience, availability and ease of adjustment over other beam splitting methods. Comparison of stability measurements made with the AS-EBS, WS-PSBS, and other beam splitters is presented.
Splitting Neutrino masses and Showering into Sky
NASA Astrophysics Data System (ADS)
Fargion, D.; D'Armiento, D.; Lanciano, O.; Oliva, P.; Iacobelli, M.; de Sanctis Lucentini, P. G.; Grossi, M.; de Santis, M.
2007-06-01
Neutrino masses might be as light as a few time the atmospheric neutrino mass splitting. The relic cosmic neutrinos may cluster in wide Dark Hot Local Group Halo. High Energy ZeV cosmic neutrinos (in Z-Showering model) might hit relic ones at each mass in different resonance energies in our nearby Universe. This non-degenerated density and energy must split UHE Z-boson secondaries (in Z-Burst model) leading to multi injection of UHECR nucleons within future extreme AUGER energy. Secondaries of Z-Burst as neutral gamma, below a few tens EeV are better surviving local GZK cut-off and they might explain recent Hires BL-Lac UHECR correlations at small angles. A different high energy resonance must lead to Glashow's anti-neutrino showers while hitting electrons in matter. In water and ice it leads to isotropic light explosions. In air, Glashow's anti-neutrino showers lead to collimated and directional air-showers offering a new Neutrino Astronomy. Because of neutrino flavor mixing, astrophysical energetic tau neutrino above tens GeV must arise over atmospheric background. At TeV range is difficult to disentangle tau neutrinos from other atmospheric flavors. At greater energy around PeV, Tau escaping mountains and Earth and decaying in flight are effectively showering in air sky. These Horizontal showering is splitting by geomagnetic field in forked shapes. Such air-showers secondaries release amplified and beamed gamma bursts (like observed TGF), made also by muon and electron pair bundles, with their accompanying rich Cherenkov flashes. Also planet's largest (Saturn, Jupiter) atmosphere limbs offer an ideal screen for UHE GZK and Z-burst tau neutrino, because their largest sizes. Titan thick atmosphere and small radius are optimal for discovering up-going resonant Glashow resonant anti-neutrino electron showers. Detection from Earth of Tau, anti-Tau, anti-electron neutrino induced Air-showers by twin Magic Telescopes on top mountains, or space based detection on
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.
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.
Yao, Jincao; Yu, Huimin; Hu, Roland
2017-01-01
This paper introduces a new implicit-kernel-sparse-shape-representation-based object segmentation framework. Given an input object whose shape is similar to some of the elements in the training set, the proposed model can automatically find a cluster of implicit kernel sparse neighbors to approximately represent the input shape and guide the segmentation. A distance-constrained probabilistic definition together with a dualization energy term is developed to connect high-level shape representation and low-level image information. We theoretically prove that our model not only derives from two projected convex sets but is also equivalent to a sparse-reconstruction-error-based representation in the Hilbert space. Finally, a "wake-sleep"-based segmentation framework is applied to drive the evolutionary curve to recover the original shape of the object. We test our model on two public datasets. Numerical experiments on both synthetic images and real applications show the superior capabilities of the proposed framework.
NASA Astrophysics Data System (ADS)
Chang, Yong; Zi, Yanyang; Zhao, Jiyuan; Yang, Zhe; He, Wangpeng; Sun, Hailiang
2017-03-01
In guided wave pipeline inspection, echoes reflected from closely spaced reflectors generally overlap, meaning useful information is lost. To solve the overlapping problem, sparse deconvolution methods have been developed in the past decade. However, conventional sparse deconvolution methods have limitations in handling guided wave signals, because the input signal is directly used as the prototype of the convolution matrix, without considering the waveform change caused by the dispersion properties of the guided wave. In this paper, an adaptive sparse deconvolution (ASD) method is proposed to overcome these limitations. First, the Gaussian echo model is employed to adaptively estimate the column prototype of the convolution matrix instead of directly using the input signal as the prototype. Then, the convolution matrix is constructed upon the estimated results. Third, the split augmented Lagrangian shrinkage (SALSA) algorithm is introduced to solve the deconvolution problem with high computational efficiency. To verify the effectiveness of the proposed method, guided wave signals obtained from pipeline inspection are investigated numerically and experimentally. Compared to conventional sparse deconvolution methods, e.g. the {{l}1} -norm deconvolution method, the proposed method shows better performance in handling the echo overlap problem in the guided wave signal.
Adaptive feature extraction using sparse coding for machinery fault diagnosis
NASA Astrophysics Data System (ADS)
Liu, Haining; Liu, Chengliang; Huang, Yixiang
2011-02-01
In the signal processing domain, there has been growing interest in sparse coding with a learned dictionary instead of a predefined one, which is advocated as an effective mathematical description for the underlying principle of mammalian sensory systems in processing information. In this paper, sparse coding is introduced as a feature extraction technique for machinery fault diagnosis and an adaptive feature extraction scheme is proposed based on it. The two core problems of sparse coding, i.e., dictionary learning and coefficients solving, are discussed in detail. A natural extension of sparse coding, shift-invariant sparse coding, is also introduced. Then, the vibration signals of rolling element bearings are taken as the target signals to verify the proposed scheme, and shift-invariant sparse coding is used for vibration analysis. With the purpose of diagnosing the different fault conditions of bearings, features are extracted following the proposed scheme: basis functions are separately learned from each class of vibration signals trying to capture the defective impulses; a redundant dictionary is built by merging all the learned basis functions; based on the redundant dictionary, the diagnostic information is made explicit in the solved sparse representations of vibration signals; sparse features are formulated in terms of activations of atoms. The multiclass linear discriminant analysis (LDA) classifier is used to test the discriminability of the extracted sparse features and the adaptability of the learned atoms. The experiments show that sparse coding is an effective feature extraction technique for machinery fault diagnosis.
Stochastic convex sparse principal component analysis.
Baytas, Inci M; Lin, Kaixiang; Wang, Fei; Jain, Anil K; Zhou, Jiayu
2016-12-01
Principal component analysis (PCA) is a dimensionality reduction and data analysis tool commonly used in many areas. The main idea of PCA is to represent high-dimensional data with a few representative components that capture most of the variance present in the data. However, there is an obvious disadvantage of traditional PCA when it is applied to analyze data where interpretability is important. In applications, where the features have some physical meanings, we lose the ability to interpret the principal components extracted by conventional PCA because each principal component is a linear combination of all the original features. For this reason, sparse PCA has been proposed to improve the interpretability of traditional PCA by introducing sparsity to the loading vectors of principal components. The sparse PCA can be formulated as an ℓ1 regularized optimization problem, which can be solved by proximal gradient methods. However, these methods do not scale well because computation of the exact gradient is generally required at each iteration. Stochastic gradient framework addresses this challenge by computing an expected gradient at each iteration. Nevertheless, stochastic approaches typically have low convergence rates due to the high variance. In this paper, we propose a convex sparse principal component analysis (Cvx-SPCA), which leverages a proximal variance reduced stochastic scheme to achieve a geometric convergence rate. We further show that the convergence analysis can be significantly simplified by using a weak condition which allows a broader class of objectives to be applied. The efficiency and effectiveness of the proposed method are demonstrated on a large-scale electronic medical record cohort.
Learn Sparse Dictionaries for Edit Propagation.
Xiaowu Chen; Jianwei Li; Dongqing Zou; Qinping Zhao
2016-04-01
With the increasing availability of high-resolution images, videos, and 3D models, the demand for scalable large data processing techniques increases. We introduce a method of sparse dictionary learning for edit propagation of large input data. Previous approaches for edit propagation typically employ a global optimization over the whole set of pixels (or vertexes), incurring a prohibitively high memory and time-consumption for large input data. Rather than propagating an edit pixel by pixel, we follow the principle of sparse representation to obtain a representative and compact dictionary and perform edit propagation on the dictionary instead. The sparse dictionary provides an intrinsic basis for input data, and the coding coefficients capture the linear relationship between all pixels and the dictionary atoms. The learned dictionary is then optimized by a novel scheme, which maximizes the Kullback-Leibler divergence between each atom pair to remove redundant atoms. To enable local edit propagation for images or videos with similar appearance, a dictionary learning strategy is proposed by considering range constraint to better account for the global distribution of pixels in their feature space. We show several applications of the sparsity-based edit propagation, including video recoloring, theme editing, and seamless cloning, operating on both color and texture features. Our approach can also be applied to computer graphics tasks, such as 3D surface deformation. We demonstrate that with an atom-to-pixel ratio in the order of 0.01% signifying a significant reduction on memory consumption, our method still maintains a high degree of visual fidelity.
Space-Time Approximation with Sparse Grids
Griebel, M; Oeltz, D; Vassilevski, P S
2005-04-14
In this article we introduce approximation spaces for parabolic problems which are based on the tensor product construction of a multiscale basis in space and a multiscale basis in time. Proper truncation then leads to so-called space-time sparse grid spaces. For a uniform discretization of the spatial space of dimension d with O(N{sup d}) degrees of freedom, these spaces involve for d > 1 also only O(N{sup d}) degrees of freedom for the discretization of the whole space-time problem. But they provide the same approximation rate as classical space-time Finite Element spaces which need O(N{sup d+1}) degrees of freedoms. This makes these approximation spaces well suited for conventional parabolic and for time-dependent optimization problems. We analyze the approximation properties and the dimension of these sparse grid space-time spaces for general stable multiscale bases. We then restrict ourselves to an interpolatory multiscale basis, i.e. a hierarchical basis. Here, to be able to handle also complicated spatial domains {Omega}, we construct the hierarchical basis from a given spatial Finite Element basis as follows: First we determine coarse grid points recursively over the levels by the coarsening step of the algebraic multigrid method. Then, we derive interpolatory prolongation operators between the respective coarse and fine grid points by a least squares approach. This way we obtain an algebraic hierarchical basis for the spatial domain which we then use in our space-time sparse grid approach. We give numerical results on the convergence rate of the interpolation error of these spaces for various space-time problems with two spatial dimensions. Also implementational issues, data structures and questions of adaptivity are addressed to some extent.
The application of low-rank and sparse decomposition method in the field of climatology
NASA Astrophysics Data System (ADS)
Gupta, Nitika; Bhaskaran, Prasad K.
2017-03-01
The present study reports a low-rank and sparse decomposition method that separates the mean and the variability of a climate data field. Until now, the application of this technique was limited only in areas such as image processing, web data ranking, and bioinformatics data analysis. In climate science, this method exactly separates the original data into a set of low-rank and sparse components, wherein the low-rank components depict the linearly correlated dataset (expected or mean behavior), and the sparse component represents the variation or perturbation in the dataset from its mean behavior. The study attempts to verify the efficacy of this proposed technique in the field of climatology with two examples of real world. The first example attempts this technique on the maximum wind-speed (MWS) data for the Indian Ocean (IO) region. The study brings to light a decadal reversal pattern in the MWS for the North Indian Ocean (NIO) during the months of June, July, and August (JJA). The second example deals with the sea surface temperature (SST) data for the Bay of Bengal region that exhibits a distinct pattern in the sparse component. The study highlights the importance of the proposed technique used for interpretation and visualization of climate data.
The comparison of OPC performance and run time for dense versus sparse solutions
NASA Astrophysics Data System (ADS)
Abdo, Amr; Stobert, Ian; Viswanathan, Ramya; Burns, Ryan; Herold, Klaus; Kallingal, Chidam; Meiring, Jason; Oberschmidt, James; Mansfield, Scott
2008-03-01
The lithographic processes and resolution enhancement techniques (RET) needed to achieve pattern fidelity are becoming more complicated as the required critical dimensions (CDs) shrink. For technology nodes with smaller devices and tolerances, more complex models and proximity corrections are needed and these significantly increase the computational requirements. New simulation techniques are required to address these computational challenges. The new simulation technique we focus on in this work is dense optical proximity correction (OPC). Sparse OPC tools typically require a laborious, manual and time consuming OPC optimization approach. In contrast, dense OPC uses pixel-based simulation that does not need as much manual setup. Dense OPC was introduced because sparse simulation methodology causes run times to explode as the pattern density increases, since the number of simulation sites in a given optical radius increases. In this work, we completed a comparison of the OPC modeling performance and run time for the dense and the sparse solutions. The analysis found the computational run time to be highly design dependant. The result should lead to the improvement of the quality and performance of the OPC solution and shed light on the pros and cons of using dense versus sparse solution. This will help OPC engineers to decide which solution to apply to their particular situation.
Torsional Split Hopkinson Bar Optimization
2012-04-10
is the torsional wave speed . Also, one can relate the torque with the yield stress of the material, as seen in equation 2; where r is the radius of...be equal to the mechanical impedance of the bars. In other words, the product of density, speed of wave and polar moment of inertia must remain...pillow blocks used to mount the incident and transmitter bars are cast iron based- mounted Babbitt-lined bearing split, for 1 in. shaft diameter
Low frequency split cycle cryocooler
NASA Technical Reports Server (NTRS)
Bian, S. X.; Zhang, Y. D.; Wan, W. W.; Wang, L.; Hu, Q. C.
1985-01-01
A split cycle Stirling cryocooler with two different drive motors and operating at a low drive frequency can have high thermodynamic efficiency. The temperature of the cold end of the cryocooler varies with drive frequency, voltage of the input electrical power and initial charge pressure values. The cryocooler operating at 8 Hz can provide 7 watts of refrigeration at 77 K for 230 watts of electrical input power.
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...
10 CFR 26.135 - Split specimens.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 10 Energy 1 2011-01-01 2011-01-01 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, 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...
Development of a new flux splitting scheme
NASA Technical Reports Server (NTRS)
Liou, Meng-Sing; Steffen, Christopher J., Jr.
1991-01-01
The successful use of a novel splitting scheme, the advection upstream splitting method, for model aerodynamic problems where Van Leer and Roe schemes had failed previously is discussed. The present scheme is based on splitting in which the convective and pressure terms are separated and treated differently depending on the underlying physical conditions. The present method is found to be both simple and accurate.
Development of a new flux splitting scheme
NASA Technical Reports Server (NTRS)
Liou, Meng-Sing; Steffen, Christopher J., Jr.
1991-01-01
The use of a new splitting scheme, the advection upstream splitting method, for model aerodynamic problems where Van Leer and Roe schemes had failed previously is discussed. The present scheme is based on splitting in which the convective and pressure terms are separated and treated differently depending on the underlying physical conditions. The present method is found to be both simple and accurate.
All scale-free networks are sparse.
Del Genio, Charo I; Gross, Thilo; Bassler, Kevin E
2011-10-21
We study the realizability of scale-free networks with a given degree sequence, showing that the fraction of realizable sequences undergoes two first-order transitions at the values 0 and 2 of the power-law exponent. We substantiate this finding by analytical reasoning and by a numerical method, proposed here, based on extreme value arguments, which can be applied to any given degree distribution. Our results reveal a fundamental reason why large scale-free networks without constraints on minimum and maximum degree must be sparse.
Effective dimension reduction for sparse functional data.
Yao, F; Lei, E; Wu, Y
2015-06-01
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.
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
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.
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.
Partitioning sparse rectangular matrices for parallel processing
Kolda, T.G.
1998-05-01
The authors are interested in partitioning sparse rectangular matrices for parallel processing. The partitioning problem has been well-studied in the square symmetric case, but the rectangular problem has received very little attention. They will formalize the rectangular matrix partitioning problem and discuss several methods for solving it. They will extend the spectral partitioning method for symmetric matrices to the rectangular case and compare this method to three new methods -- the alternating partitioning method and two hybrid methods. The hybrid methods will be shown to be best.
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
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.
Testing split supersymmetry with inflation
NASA Astrophysics Data System (ADS)
Craig, Nathaniel; Green, Daniel
2014-07-01
Split supersymmetry (SUSY) — in which SUSY is relevant to our universe but largely inaccessible at current accelerators — has become increasingly plausible given the absence of new physics at the LHC, the success of gauge coupling unification, and the observed Higgs mass. Indirect probes of split SUSY such as electric dipole moments (EDMs) and flavor violation offer hope for further evidence but are ultimately limited in their reach. Inflation offers an alternate window into SUSY through the direct production of superpartners during inflation. These particles are capable of leaving imprints in future cosmological probes of primordial non-gaussianity. Given the recent observations of BICEP2, the scale of inflation is likely high enough to probe the full range of split SUSY scenarios and therefore offers a unique advantage over low energy probes. The key observable for future experiments is equilateral non-gaussianity, which will be probed by both cosmic microwave background (CMB) and large scale structure (LSS) surveys. In the event of a detection, we forecast our ability to find evidence for superpartners through the scaling behavior in the squeezed limit of the bispectrum.
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.
Status of air-shower measurements with sparse radio arrays
NASA Astrophysics Data System (ADS)
Schröder, Frank G.
2017-03-01
This proceeding gives a summary of the current status and open questions of the radio technique for cosmic-ray air showers, assuming that the reader is already familiar with the principles. It includes recent results of selected experiments not present at this conference, e.g., LOPES and TREND. Current radio arrays like AERA or Tunka-Rex have demonstrated that areas of several km2 can be instrumented for reasonable costs with antenna spacings of the order of 200m. For the energy of the primary particle such sparse antenna arrays can already compete in absolute accuracy with other precise techniques, like the detection of air-fluorescence or air-Cherenkov light. With further improvements in the antenna calibration, the radio detection might become even more accurate. For the atmospheric depth of the shower maximum, Xmax, currently only the dense array LOFAR features a precision similar to the fluorescence technique, but analysis methods for the radio measurement of Xmax are still under development. Moreover, the combination of radio and muon measurements is expected to increase the accuracy of the mass composition, and this around-the-clock recording is not limited to clear nights as are the light-detection methods. Consequently, radio antennas will be a valuable add-on for any air shower array targeting the energy range above 100 PeV.
Tantalum-based semiconductors for solar water splitting.
Zhang, Peng; Zhang, Jijie; Gong, Jinlong
2014-07-07
Solar energy utilization is one of the most promising solutions for the energy crises. Among all the possible means to make use of solar energy, solar water splitting is remarkable since it can accomplish the conversion of solar energy into chemical energy. The produced hydrogen is clean and sustainable which could be used in various areas. For the past decades, numerous efforts have been put into this research area with many important achievements. Improving the overall efficiency and stability of semiconductor photocatalysts are the research focuses for the solar water splitting. Tantalum-based semiconductors, including tantalum oxide, tantalate and tantalum (oxy)nitride, are among the most important photocatalysts. Tantalum oxide has the band gap energy that is suitable for the overall solar water splitting. The more negative conduction band minimum of tantalum oxide provides photogenerated electrons with higher potential for the hydrogen generation reaction. Tantalates, with tunable compositions, show high activities owning to their layered perovskite structure. (Oxy)nitrides, especially TaON and Ta3N5, have small band gaps to respond to visible-light, whereas they can still realize overall solar water splitting with the proper positions of conduction band minimum and valence band maximum. This review describes recent progress regarding the improvement of photocatalytic activities of tantalum-based semiconductors. Basic concepts and principles of solar water splitting will be discussed in the introduction section, followed by the three main categories regarding to the different types of tantalum-based semiconductors. In each category, synthetic methodologies, influencing factors on the photocatalytic activities, strategies to enhance the efficiencies of photocatalysts and morphology control of tantalum-based materials will be discussed in detail. Future directions to further explore the research area of tantalum-based semiconductors for solar water splitting
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.
Neonatal atlas construction using sparse representation.
Shi, Feng; Wang, Li; Wu, Guorong; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang
2014-09-01
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.
Protein family classification using sparse markov transducers.
Eskin, Eleazar; Noble, William Stafford; Singer, Yoram
2003-01-01
We present a method for classifying proteins into families based on short subsequences of amino acids using a new probabilistic model called sparse Markov transducers (SMT). We classify a protein by estimating probability distributions over subsequences of amino acids from the protein. Sparse Markov transducers, similar to probabilistic suffix trees, estimate a probability distribution conditioned on an input sequence. SMTs generalize probabilistic suffix trees by allowing for wild-cards in the conditioning sequences. Since substitutions of amino acids are common in protein families, incorporating wild-cards into the model significantly improves classification performance. We present two models for building protein family classifiers using SMTs. As protein databases become larger, data driven learning algorithms for probabilistic models such as SMTs will require vast amounts of memory. We therefore describe and use efficient data structures to improve the memory usage of SMTs. We evaluate SMTs by building protein family classifiers using the Pfam and SCOP databases and compare our results to previously published results and state-of-the-art protein homology detection methods. SMTs outperform previous probabilistic suffix tree methods and under certain conditions perform comparably to state-of-the-art protein homology methods.
Sparse spectrum model for a turbulent phase.
Charnotskii, Mikhail
2013-03-01
Monte Carlo (MC) simulation of phase front perturbations by atmospheric turbulence finds numerous applications for design and modeling of the adaptive optics systems, laser beam propagation simulations, and evaluating the performance of the various optical systems operating in the open air environment. Accurate generation of two-dimensional random fields of turbulent phase is complicated by the enormous diversity of scales that can reach five orders of magnitude in each coordinate. In addition there is a need for generation of the long "ribbons" of turbulent phase that are used to represent the time evolution of the wave front. This makes it unfeasible to use the standard discrete Fourier transform-based technique as a basis for the MC simulation algorithm. We propose a new model for turbulent phase: the sparse spectrum (SS) random field. The principal assumption of the SS model is that each realization of the random field has a discrete random spectral support. Statistics of the random amplitudes and wave vectors of the SS model are arranged to provide the required spectral and correlation properties of the random field. The SS-based MC model offers substantial reduction of computer costs for simulation of the wide-band random fields and processes, and is capable of generating long aperiodic phase "ribbons." We report the results of model trials that determine the number of sparse components, and the range of wavenumbers that is necessary to accurately reproduce the random field with a power-law spectrum.
Image reconstruction from photon sparse data
Mertens, Lena; Sonnleitner, Matthias; Leach, Jonathan; Agnew, Megan; Padgett, Miles J.
2017-01-01
We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected. PMID:28169363
Image reconstruction from photon sparse data
NASA Astrophysics Data System (ADS)
Mertens, Lena; Sonnleitner, Matthias; Leach, Jonathan; Agnew, Megan; Padgett, Miles J.
2017-02-01
We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected.
Sparse estimation of a covariance matrix.
Bien, Jacob; Tibshirani, Robert J
2011-12-01
We suggest a method for estimating a covariance matrix on the basis of a sample of vectors drawn from a multivariate normal distribution. In particular, we penalize the likelihood with a lasso penalty on the entries of the covariance matrix. This penalty plays two important roles: it reduces the effective number of parameters, which is important even when the dimension of the vectors is smaller than the sample size since the number of parameters grows quadratically in the number of variables, and it produces an estimate which is sparse. In contrast to sparse inverse covariance estimation, our method's close relative, the sparsity attained here is in the covariance matrix itself rather than in the inverse matrix. Zeros in the covariance matrix correspond to marginal independencies; thus, our method performs model selection while providing a positive definite estimate of the covariance. The proposed penalized maximum likelihood problem is not convex, so we use a majorize-minimize approach in which we iteratively solve convex approximations to the original nonconvex problem. We discuss tuning parameter selection and demonstrate on a flow-cytometry dataset how our method produces an interpretable graphical display of the relationship between variables. We perform simulations that suggest that simple elementwise thresholding of the empirical covariance matrix is competitive with our method for identifying the sparsity structure. Additionally, we show how our method can be used to solve a previously studied special case in which a desired sparsity pattern is prespecified.
Learning doubly sparse transforms for images.
Ravishankar, Saiprasad; Bresler, Yoram
2013-12-01
The sparsity of images in a transform domain or dictionary has been exploited in many applications in image processing. For example, analytical sparsifying transforms, such as wavelets and discrete cosine transform (DCT), have been extensively used in compression standards. Recently, synthesis sparsifying dictionaries that are directly adapted to the data have become popular especially in applications such as image denoising. Following up on our recent research, where we introduced the idea of learning square sparsifying transforms, we propose here novel problem formulations for learning doubly sparse transforms for signals or image patches. These transforms are a product of a fixed, fast analytic transform such as the DCT, and an adaptive matrix constrained to be sparse. Such transforms can be learnt, stored, and implemented efficiently. We show the superior promise of our learnt transforms as compared with analytical sparsifying transforms such as the DCT for image representation. We also show promising performance in image denoising that compares favorably with approaches involving learnt synthesis dictionaries such as the K-SVD algorithm. The proposed approach is also much faster than K-SVD denoising.
Sparse Identification of Nonlinear Dynamics (SINDy)
NASA Astrophysics Data System (ADS)
Brunton, Steven; Proctor, Joshua; Kutz, Nathan
2016-11-01
This work develops a general new framework to discover the governing equations underlying a dynamical system simply from data measurements, leveraging advances in sparsity techniques and machine learning. The so-called sparse identification of nonlinear dynamics (SINDy) method results in models that are parsimonious, balancing model complexity with descriptive ability while avoiding over fitting. The only assumption about the structure of the model is that there are only a few important terms that govern the dynamics, so that the equations are sparse in the space of possible functions; this assumption holds for many physical systems in an appropriate basis. We demonstrate the algorithm on a wide range of problems, from simple canonical systems, including the chaotic Lorenz system, to the canonical fluid vortex shedding behind an circular cylinder at Re=100. We also show that this method generalizes to parameterized systems and systems that are time-varying or have external forcing. With abundant data and elusive laws, data-driven discovery of dynamics will continue to play an increasingly important role in the characterization and control of fluid dynamics.
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.
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.
Sparse and accurate high resolution SAR imaging
NASA Astrophysics Data System (ADS)
Vu, Duc; Zhao, Kexin; Rowe, William; Li, Jian
2012-05-01
We investigate the usage of an adaptive method, the Iterative Adaptive Approach (IAA), in combination with a maximum a posteriori (MAP) estimate to reconstruct high resolution SAR images that are both sparse and accurate. IAA is a nonparametric weighted least squares algorithm that is robust and user parameter-free. IAA has been shown to reconstruct SAR images with excellent side lobes suppression and high resolution enhancement. We first reconstruct the SAR images using IAA, and then we enforce sparsity by using MAP with a sparsity inducing prior. By coupling these two methods, we can produce a sparse and accurate high resolution image that are conducive for feature extractions and target classification applications. In addition, we show how IAA can be made computationally efficient without sacrificing accuracies, a desirable property for SAR applications where the size of the problems is quite large. We demonstrate the success of our approach using the Air Force Research Lab's "Gotcha Volumetric SAR Data Set Version 1.0" challenge dataset. Via the widely used FFT, individual vehicles contained in the scene are barely recognizable due to the poor resolution and high side lobe nature of FFT. However with our approach clear edges, boundaries, and textures of the vehicles are obtained.
Image reconstruction from photon sparse data.
Mertens, Lena; Sonnleitner, Matthias; Leach, Jonathan; Agnew, Megan; Padgett, Miles J
2017-02-07
We report an algorithm for reconstructing images when the average number of photons recorded per pixel is of order unity, i.e. photon-sparse data. The image optimisation algorithm minimises a cost function incorporating both a Poissonian log-likelihood term based on the deviation of the reconstructed image from the measured data and a regularization-term based upon the sum of the moduli of the second spatial derivatives of the reconstructed image pixel intensities. The balance between these two terms is set by a bootstrapping technique where the target value of the log-likelihood term is deduced from a smoothed version of the original data. When compared to the original data, the processed images exhibit lower residuals with respect to the true object. We use photon-sparse data from two different experimental systems, one system based on a single-photon, avalanche photo-diode array and the other system on a time-gated, intensified camera. However, this same processing technique could most likely be applied to any low photon-number image irrespective of how the data is collected.
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
Improving sparse representation algorithms for maritime video processing
NASA Astrophysics Data System (ADS)
Smith, L. N.; Nichols, J. M.; Waterman, J. R.; Olson, C. C.; Judd, K. P.
2012-06-01
We present several improvements to published algorithms for sparse image modeling with the goal of improving processing of imagery of small watercraft in littoral environments. The first improvement is to the K-SVD algorithm for training over-complete dictionaries, which are used in sparse representations. It is shown that the training converges significantly faster by incorporating multiple dictionary (i.e., codebook) update stages in each training iteration. The paper also provides several useful and practical lessons learned from our experience with sparse representations. Results of three applications of sparse representation are presented and compared to the state-of-the-art methods; image compression, image denoising, and super-resolution.
Local structure preserving sparse coding for infrared target recognition
Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa
2017-01-01
Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824
Multimodal visual dictionary learning via heterogeneous latent semantic sparse coding
NASA Astrophysics Data System (ADS)
Li, Chenxiao; Ding, Guiguang; Zhou, Jile; Guo, Yuchen; Liu, Qiang
2014-11-01
Visual dictionary learning as a crucial task of image representation has gained increasing attention. Specifically, sparse coding is widely used due to its intrinsic advantage. In this paper, we propose a novel heterogeneous latent semantic sparse coding model. The central idea is to bridge heterogeneous modalities by capturing their common sparse latent semantic structure so that the learned visual dictionary is able to describe both the visual and textual properties of training data. Experiments on both image categorization and retrieval tasks demonstrate that our model shows superior performance over several recent methods such as K-means and Sparse Coding.
Photoelectrochemical water splitting at titanium dioxide nanotubes coated with tungsten trioxide
NASA Astrophysics Data System (ADS)
Park, Jong Hyeok; Park, O. Ok; Kim, Sungwook
2006-10-01
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 150mW/cm2, hydrogen gas generated at the overall conversion efficiency of 0.87%.
NASA Astrophysics Data System (ADS)
Feng, Shuai; Xiao, Ting-Hui; Gan, Lin; Wang, Yi-Quan
2017-01-01
Light-beam-splitting characteristics are theoretically and experimentally studied in 2D square-lattice photonic crystals (PhCs) with delicately designed and modulated output surfaces. Compared with the traditional branch-waveguide and self-collimation-type PhC splitters, our proposed structure can not only split the input light beam into different numbers of branches but also realize the adjustment of their relative light intensities in each branch. Moreover, the influence of a light beam’s incident angle on both the output branch beams’ relative intensity and propagation direction is investigated. This proposed light beam splitter is able to work within a broad frequency range, and the propagation directions of the output split beams can be modified with the incident beam’s frequency. In addition, when the PhC device becomes thicker, a kind of light-beam-focusing phenomenon is observed. Advantageously, our light-beam-splitting device has no restriction as to the incident light beam’s location and width, so it is much more convenient and practical for achieving optical connection with other functional devices in complicated, large-scale, all-optical integrated circuits.
Controlled synthesis of GaN-based nanowires for photoelectrochemical water splitting applications
NASA Astrophysics Data System (ADS)
Ebaid, Mohamed; Kang, Jin-Ho; Ryu, Sang-Wan
2017-01-01
Photoelectrochemical (PEC) water splitting using semiconductor materials as light absorbers have been extensively studied. Several semiconducting materials have been proposed, such as TiO2, ZnO, and GaN. Because the efficiency of PEC water splitting is dependent on visible light absorption, the ability to tune the bandgap of GaN by alloying with In makes it advantageous over other wide bandgap semiconductors. The fabrication of GaN-based materials with nanoscale geometry offers more merit for their use in PEC water splitting. In this review, we provide an overview of the recent progress made in the synthesis and application of GaN-based nanomaterials in PEC water splitting. The outstanding challenges and the future prospects of this field will also be addressed.
Split Dirac Supersymmetry: An Ultraviolet Completion of Higgsino Dark Matter
Fox, Patrick J.; Kribs, Graham D.; Martin, Adam
2014-10-07
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 $\\sim 10^{8-11}$ 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 $\\gtrsim 10^{17}$ GeV. The $\\mu$-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.
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
ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.
Fan, Jianqing; Rigollet, Philippe; Wang, Weichen
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 ℓ r 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.
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.
Surface reconstruction from sparse fringe contours
Cong, G.; Parvin, B.
1998-08-10
A new approach for reconstruction of 3D surfaces from 2D cross-sectional contours is presented. By using the so-called ''Equal Importance Criterion,'' we reconstruct the surface based on the assumption that every point in the region contributes equally to the surface reconstruction process. In this context, the problem is formulated in terms of a partial differential equation (PDE), and we show that the solution for dense contours can be efficiently derived from distance transform. In the case of sparse contours, we add a regularization term to insure smoothness in surface recovery. The proposed technique allows for surface recovery at any desired resolution. The main advantage of the proposed method is that inherent problems due to correspondence, tiling, and branching are avoided. Furthermore, the computed high resolution surface is better represented for subsequent geometric analysis. We present results on both synthetic and real data.
Preserving sparseness in multivariate polynominal factorization
NASA Technical Reports Server (NTRS)
Wang, P. S.
1977-01-01
Attempts were made to factor these ten polynomials on MACSYMA. However it did not get very far with any of the larger polynomials. At that time, MACSYMA used an algorithm created by Wang and Rothschild. This factoring algorithm was also implemented for the symbolic manipulation system, SCRATCHPAD of IBM. A closer look at this old factoring algorithm revealed three problem areas, each of which contribute to losing sparseness and intermediate expression growth. This study led to effective ways of avoiding these problems and actually to a new factoring algorithm. The three problems are known as the extraneous factor problem, the leading coefficient problem, and the bad zero problem. These problems are examined separately. Their causes and effects are set forth in detail; the ways to avoid or lessen these problems are described.
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
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
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).
Classification of sparse high-dimensional vectors.
Ingster, Yuri I; Pouet, Christophe; Tsybakov, Alexandre B
2009-11-13
We study the problem of classification of d-dimensional vectors into two classes (one of which is 'pure noise') based on a training sample of size m. The main specific feature is that the dimension d can be very large. We suppose that the difference between the distribution of the population and that of the noise is only in a shift, which is a sparse vector. For Gaussian noise, fixed sample size m, and dimension d that tends to infinity, we obtain the sharp classification boundary, i.e. the necessary and sufficient conditions for the possibility of successful classification. We propose classifiers attaining this boundary. We also give extensions of the result to the case where the sample size m depends on d and satisfies the condition (log m)/log d --> gamma, 0
A scalable sparse eigensolver for petascale applications
NASA Astrophysics Data System (ADS)
Keceli, Murat; Zhang, Hong; Zapol, Peter; Dixon, David; Wagner, Albert
2015-03-01
Exploiting locality of chemical interactions and therefore sparsity is necessary to push the limits of quantum simulations beyond petascale. However, sparse numerical algorithms are known to have poor strong scaling. Here, we show that shift-and-invert parallel spectral transformations (SIPs) method can scale up to two-hundred thousand cores for density functional based tight-binding (DFTB), or semi-empirical molecular orbital (SEMO) applications. We demonstrated the robustness and scalability of the SIPs method on various kinds of systems including metallic carbon nanotubes, diamond crystals and water clusters. We analyzed how sparsity patterns and eigenvalue spectrums of these different type of applications affect the computational performance of the SIPs. The SIPs method enables us to perform simulations with more than five hundred thousands of basis functions utilizing more than hundreds of thousands of cores. SIPs has a better scaling for memory and computational time in contrast to dense eigensolvers, and it does not require fast interconnects.
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.
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.
Bhave, Sampada; Lingala, Sajan Goud; Jacob, Mathews
2014-01-01
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 over conventional CS schemes, while achieving convergence speed up factors of over 10 fold over the previously proposed implementation of the BCS algorithm.
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.
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.
A proximal iteration for deconvolving Poisson noisy images using sparse representations.
Dupé, François-Xavier; Fadili, Jalal M; Starck, Jean-Luc
2009-02-01
We propose an image deconvolution algorithm when the data is contaminated by Poisson noise. The image to restore is assumed to be sparsely represented in a dictionary of waveforms such as the wavelet or curvelet transforms. Our key contributions are as follows. First, we handle the Poisson noise properly by using the Anscombe variance stabilizing transform leading to a nonlinear degradation equation with additive Gaussian noise. Second, the deconvolution problem is formulated as the minimization of a convex functional with a data-fidelity term reflecting the noise properties, and a nonsmooth sparsity-promoting penalty over the image representation coefficients (e.g., l(1) -norm). An additional term is also included in the functional to ensure positivity of the restored image. Third, a fast iterative forward-backward splitting algorithm is proposed to solve the minimization problem. We derive existence and uniqueness conditions of the solution, and establish convergence of the iterative algorithm. Finally, a GCV-based model selection procedure is proposed to objectively select the regularization parameter. Experimental results are carried out to show the striking benefits gained from taking into account the Poisson statistics of the noise. These results also suggest that using sparse-domain regularization may be tractable in many deconvolution applications with Poisson noise such as astronomy and microscopy.
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.
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.
Blind spectral unmixing based on sparse nonnegative matrix factorization.
Yang, Zuyuan; Zhou, Guoxu; Xie, Shengli; Ding, Shuxue; Yang, Jun-Mei; Zhang, Jun
2011-04-01
Nonnegative matrix factorization (NMF) is a widely used method for blind spectral unmixing (SU), which aims at obtaining the endmembers and corresponding fractional abundances, knowing only the collected mixing spectral data. It is noted that the abundance may be sparse (i.e., the endmembers may be with sparse distributions) and sparse NMF tends to lead to a unique result, so it is intuitive and meaningful to constrain NMF with sparseness for solving SU. However, due to the abundance sum-to-one constraint in SU, the traditional sparseness measured by L0/L1-norm is not an effective constraint any more. A novel measure (termed as S-measure) of sparseness using higher order norms of the signal vector is proposed in this paper. It features the physical significance. By using the S-measure constraint (SMC), a gradient-based sparse NMF algorithm (termed as NMF-SMC) is proposed for solving the SU problem, where the learning rate is adaptively selected, and the endmembers and abundances are simultaneously estimated. In the proposed NMF-SMC, there is no pure index assumption and no need to know the exact sparseness degree of the abundance in prior. Yet, it does not require the preprocessing of dimension reduction in which some useful information may be lost. Experiments based on synthetic mixtures and real-world images collected by AVIRIS and HYDICE sensors are performed to evaluate the validity of the proposed method.
Water Splitting with Series-Connected Polymer Solar Cells.
Esiner, Serkan; van Eersel, Harm; van Pruissen, Gijs W P; Turbiez, Mathieu; Wienk, Martijn M; Janssen, René A J
2016-10-12
We investigate light-driven electrochemical water splitting with series-connected polymer solar cells using a combined experimental and modeling approach. The expected maximum solar-to-hydrogen conversion efficiency (ηSTH) for light-driven water splitting is modeled for two, three, and four series-connected polymer solar cells. In the modeling, we assume an electrochemical water splitting potential of 1.50 V and a polymer solar cell for which the external quantum efficiency and fill factor are both 0.65. The minimum photon energy loss (Eloss), defined as the energy difference between the optical band gap (Eg) and the open-circuit voltage (Voc), is set to 0.8 eV, which we consider a realistic value for polymer solar cells. Within these approximations, two series-connected single junction cells with Eg = 1.73 eV or three series-connected cells with Eg = 1.44 eV are both expected to give an ηSTH of 6.9%. For four series-connected cells, the maximum ηSTH is slightly less at 6.2% at an optimal Eg = 1.33 eV. Water splitting was performed with series-connected polymer solar cells using polymers with different band gaps. PTPTIBDT-OD (Eg = 1.89 eV), PTB7-Th (Eg = 1.56 eV), and PDPP5T-2 (Eg = 1.44 eV) were blended with [70]PCBM as absorber layer for two, three, and four series-connected configurations, respectively, and provide ηSTH values of 4.1, 6.1, and 4.9% when using a retroreflective foil on top of the cell to enhance light absorption. The reasons for deviations with experiments are analyzed and found to be due to differences in Eg and Eloss. Light-driven electrochemical water splitting was also modeled for multijunction polymer solar cells with vertically stacked photoactive layers. Under identical assumptions, an ηSTH of 10.0% is predicted for multijunction cells.
Sparse representations for online-learning-based hyperspectral image compression.
Ülkü, İrem; Töreyin, Behçet Uğur
2015-10-10
Sparse models provide data representations in the fewest possible number of nonzero elements. This inherent characteristic enables sparse models to be utilized for data compression purposes. Hyperspectral data is large in size. In this paper, a framework for sparsity-based hyperspectral image compression methods using online learning is proposed. There are various sparse optimization models. A comparative analysis of sparse representations in terms of their hyperspectral image compression performance is presented. For this purpose, online-learning-based hyperspectral image compression methods are proposed using four different sparse representations. Results indicate that, independent of the sparsity models, online-learning-based hyperspectral data compression schemes yield the best compression performances for data rates of 0.1 and 0.3 bits per sample, compared to other state-of-the-art hyperspectral data compression techniques, in terms of image quality measured as average peak signal-to-noise ratio.
High Performance Split-Stirling Cooler Program
1982-09-01
7 SPLIT- STIRLING CYCLE CRYOCOOLER . ...... . . . . . 13 8 TEMPERATURE-SHOCK COMPARISON PERFORMANCE DATA, S/N 002 . . 23 9 TEMPERATURE-SHOCK...PERFORMANCE SPLIT- STIRLING "COOLER PROGRAM FINAL TECHNICAL REPORT "September 1982 Prepared for NIGHT VISION AND ELECTRO-OPTICS LABORATORI ES "Contract DAAK70...REPORT & P.Vt2OO COVERED HIGH PERFORMANCE SPLIT- STIRLING COOLER PROGRAM Final Technical Sept. 1979. - Sept. 1982 S. PERPORMING ORO. REPORT KUMMER
Pattern-oriented memory interpolation of sparse historical rainfall records
NASA Astrophysics Data System (ADS)
Matos, J. P.; Cohen Liechti, T.; Portela, M. M.; Schleiss, A. J.
2014-03-01
The pattern-oriented memory (POM) is a novel historical rainfall interpolation method that explicitly takes into account the time dimension in order to interpolate areal rainfall maps. The method is based on the idea that rainfall patterns exist and can be identified over a certain area by means of non-linear regressions. Having been previously benchmarked with a vast array of interpolation methods using proxy satellite data under different time and space availabilities, in the scope of the present contribution POM is applied to rain gauge data in order to produce areal rainfall maps. Tested over the Zambezi River Basin for the period from 1979 to 1997 (accurate satellite rainfall estimates based on spaceborne instruments are not available for dates prior to 1998), the novel pattern-oriented memory historical interpolation method has revealed itself as a better alternative than Kriging or Inverse Distance Weighing in the light of a Monte Carlo cross-validation procedure. Superior in most metrics to the other tested interpolation methods, in terms of the Pearson correlation coefficient and bias the accuracy of POM's historical interpolation results are even comparable with that of recent satellite rainfall products. The new method holds the possibility of calculating detailed and performing daily areal rainfall estimates, even in the case of sparse rain gauging grids. Besides their performance, the similarity to satellite rainfall estimates inherent to POM interpolations can contribute to substantially extend the length of the rainfall series used in hydrological models and water availability studies in remote areas.
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
2015-07-08
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.
Circularly split-ring-resonator-based frequency-reconfigurable antenna
NASA Astrophysics Data System (ADS)
Rahman, M. A.; Faruque, M. R. I.; Islam, M. T.
2017-01-01
In this paper, an antenna with frequency configurability in light of a circularly split-ring resonator (CSRR) is introduced. The proposed reconfigurable monopole antenna consists of a microstrip-fed hook-shaped structure and a CSRR having single reconfigurable split only. A new band of radiation unlike the band radiated from monopole only is observed due to magnetic coupling between the CSRR and the monopole antenna. The resonance frequency of the CSRR can be arbitrarily chosen by varying the dimension and relative position of its gap with the monopole, which leads the antenna to become reconfigurable one. By using a single switch with perfect electric conductor at the gap of CSRR cell, the effect of CSRR can be deactivated and, hence, it is possible to suppress the corresponding resonance, resulting in a frequency-reconfigurable antenna. Commercially available Computer Simulation Technology microwave studio based on finite integration technique was adopted throughout the study.
Anisotropic spin-orbit induced splitting of intersubband spin plasmons
NASA Astrophysics Data System (ADS)
Baboux, F.; Perez, F.; Ullrich, C. A.; D'Amico, I.; Gómez, J.; Bernard, M.
2013-01-01
The anisotropic splitting of intersubband spin plasmons, resulting from spin-orbit coupling, is studied by angle-resolved inelastic light scattering on a [001]-oriented GaAs/AlGaAs quantum well. Confirming theoretical predictions made in [C. A. Ullrich and M. A. Flatté, Phys. Rev. B 68, 235310 (2003)], this splitting is proven to exhibit a characteristic two-fold symmetry with the in-plane orientation, and to increase with increasing modulus of the excitation momentum. This opens the way to a more complete investigation, aiming at evidencing the existence of a collective spin-orbit field driving these excitations. Note to the reader concerning PDF file: legends and scales of figures have been completed on January 30, 2013.
Adamson, David N.; Mustafi, Debarshi; Zhang, John X. J.; Zheng, Bo; Ismagilov, Rustem F.
2006-01-01
This paper reports a method for the production of arrays of nanolitre plugs with distinct chemical compositions. One of the primary constraints on the use of plug-based microfluidics for large scale biological screening is the difficulty of fabricating arrays of chemically distinct plugs on the nanolitre scale. Here, using microfluidic devices with several T-junctions linked in series, a single input array of large (~320 nL) plugs was split to produce 16 output arrays of smaller (~20 nL) plugs; the composition and configuration of these arrays were identical to that of the input. This paper shows how the passive break-up of plugs in T-junction microchannel geometries can be used to produce a set of smaller-volume output arrays useful for chemical screening from a single large-volume array. A simple theoretical description is presented to describe splitting as a function of the Capillary number, the capillary pressure, the total pressure difference across the channel, and the geometric fluidic resistance. By accounting for these considerations, plug coalescence and plug–plug contamination can be eliminated from the splitting process and the symmetry of splitting can be preserved. Furthermore, single-outlet splitting devices were implemented with both valve- and volume-based methods for coordinating the release of output arrays. Arrays of plugs containing commercial sparse matrix screens were obtained from the presented splitting method and these arrays were used in protein crystallization trials. The techniques presented in this paper may facilitate the implementation of high-throughput chemical and biological screening. PMID:16929397
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…
ISODATA: Thresholds for splitting clusters
NASA Technical Reports Server (NTRS)
Kan, E. P. F. (Principal Investigator)
1972-01-01
The author has identified the following significant results. The parameter AD (average distance) as used in the ISODATA program was critically examined. Thresholds of AD to decide on the splitting of clusters were obtained. For the univariate case, 0.84 was established as a sound choice, after examining several simple, as well as composite, distributions and also after investigating the probability of misclassification when points have to be reassigned to the newly identified clusters. For the multivariate case, the empirical threshold (N-0.16)/square root of N was extrapolated. A final criticism on AD was that AD would lose its effectiveness as a discriminative measure for the present purpose when N was large.
Emittance compensation in split photoinjectors
NASA Astrophysics Data System (ADS)
Floettmann, Klaus
2017-01-01
The compensation of correlated emittance contributions is of primary importance to optimize the performance of high brightness photoinjectors. While only extended numerical simulations can capture the complex beam dynamics of space-charge-dominated beams in sufficient detail to optimize a specific injector layout, simplified models are required to gain a deeper understanding of the involved dynamics, to guide the optimization procedure, and to interpret experimental results. In this paper, a slice envelope model for the emittance compensation process in a split photoinjector is presented. The emittance term is included in the analytical solution of the beam envelope in a drift, which is essential to take the emittance contribution due to a beam size mismatch into account. The appearance of two emittance minima in the drift is explained, and the matching into the booster cavity is discussed. A comparison with simulation results points out effects which are not treated in the envelope model, such as overfocusing and field nonlinearities.
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.
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.
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
Method for carbon dioxide splitting
Miller, James E.; Diver, Jr., Richard B.; Siegel, Nathan P.
2017-02-28
A method for splitting carbon dioxide via a two-step metal oxide thermochemical cycle by heating a metal oxide compound selected from an iron oxide material of the general formula A.sub.xFe.sub.3-xO.sub.4, where 0.ltoreq.x.ltoreq.1 and A is a metal selected from Mg, Cu, Zn, Ni, Co, and Mn, or a ceria oxide compound of the general formula M.sub.aCe.sub.bO.sub.c, where 0
Minimal Doubling and Point Splitting
Creutz, M.
2010-06-14
Minimally-doubled chiral fermions have the unusual property of a single local field creating two fermionic species. Spreading the field over hypercubes allows construction of combinations that isolate specific modes. Combining these fields into bilinears produces meson fields of specific quantum numbers. Minimally-doubled fermion actions present the possibility of fast simulations while maintaining one exact chiral symmetry. They do, however, introduce some peculiar aspects. An explicit breaking of hyper-cubic symmetry allows additional counter-terms to appear in the renormalization. While a single field creates two different species, spreading this field over nearby sites allows isolation of specific states and the construction of physical meson operators. Finally, lattice artifacts break isospin and give two of the three pseudoscalar mesons an additional contribution to their mass. Depending on the sign of this mass splitting, one can either have a traditional Goldstone pseudoscalar meson or a parity breaking Aoki-like phase.
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.
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
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.
Prostate segmentation by sparse representation based classification
Gao, Yaozong; Liao, Shu; Shen, Dinggang
2012-01-01
Purpose: The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems. Methods: To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by
Fast sparse Raman spectral unmixing for chemical fingerprinting and quantification
NASA Astrophysics Data System (ADS)
Yaghoobi, Mehrdad; Wu, Di; Clewes, Rhea J.; Davies, Mike E.
2016-10-01
Raman spectroscopy is a well-established spectroscopic method for the detection of condensed phase chemicals. It is based on scattered light from exposure of a target material to a narrowband laser beam. The information generated enables presumptive identification from measuring correlation with library spectra. Whilst this approach is successful in identification of chemical information of samples with one component, it is more difficult to apply to spectral mixtures. The capability of handling spectral mixtures is crucial for defence and security applications as hazardous materials may be present as mixtures due to the presence of degradation, interferents or precursors. A novel method for spectral unmixing is proposed here. Most modern decomposition techniques are based on the sparse decomposition of mixture and the application of extra constraints to preserve the sum of concentrations. These methods have often been proposed for passive spectroscopy, where spectral baseline correction is not required. Most successful methods are computationally expensive, e.g. convex optimisation and Bayesian approaches. We present a novel low complexity sparsity based method to decompose the spectra using a reference library of spectra. It can be implemented on a hand-held spectrometer in near to real-time. The algorithm is based on iteratively subtracting the contribution of selected spectra and updating the contribution of each spectrum. The core algorithm is called fast non-negative orthogonal matching pursuit, which has been proposed by the authors in the context of nonnegative sparse representations. The iteration terminates when the maximum number of expected chemicals has been found or the residual spectrum has a negligible energy, i.e. in the order of the noise level. A backtracking step removes the least contributing spectrum from the list of detected chemicals and reports it as an alternative component. This feature is particularly useful in detection of chemicals
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.
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.
Sparse Superpixel Unmixing for Hyperspectral Image Analysis
NASA Technical Reports Server (NTRS)
Castano, Rebecca; Thompson, David R.; Gilmore, Martha
2010-01-01
Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.
A sparse Ising model with covariates.
Cheng, Jie; Levina, Elizaveta; Wang, Pei; Zhu, Ji
2014-12-01
There has been a lot of work fitting Ising models to multivariate binary data in order to understand the conditional dependency relationships between the variables. However, additional covariates are frequently recorded together with the binary data, and may influence the dependence relationships. Motivated by such a dataset on genomic instability collected from tumor samples of several types, we propose a sparse covariate dependent Ising model to study both the conditional dependency within the binary data and its relationship with the additional covariates. This results in subject-specific Ising models, where the subject's covariates influence the strength of association between the genes. As in all exploratory data analysis, interpretability of results is important, and we use ℓ1 penalties to induce sparsity in the fitted graphs and in the number of selected covariates. Two algorithms to fit the model are proposed and compared on a set of simulated data, and asymptotic results are established. The results on the tumor dataset and their biological significance are discussed in detail.
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 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.
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.
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.
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.
Partially sparse imaging of stationary indoor scenes
NASA Astrophysics Data System (ADS)
Ahmad, Fauzia; Amin, Moeness G.; Dogaru, Traian
2014-12-01
In this paper, we exploit the notion of partial sparsity for scene reconstruction associated with through-the-wall radar imaging of stationary targets under reduced data volume. Partial sparsity implies that the scene being imaged consists of a sparse part and a dense part, with the support of the latter assumed to be known. For the problem at hand, sparsity is represented by a few stationary indoor targets, whereas the high scene density is defined by exterior and interior walls. Prior knowledge of wall positions and extent may be available either through building blueprints or from prior surveillance operations. The contributions of the exterior and interior walls are removed from the data through the use of projection matrices, which are determined from wall- and corner-specific dictionaries. The projected data, with enhanced sparsity, is then processed using l 1 norm reconstruction techniques. Numerical electromagnetic data is used to demonstrate the effectiveness of the proposed approach for imaging stationary indoor scenes using a reduced set of measurements.
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.
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.
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
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…
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…
Splitting in Schizophrenia and Borderline Personality Disorder
Pec, Ondrej; Bob, Petr; Raboch, Jiri
2014-01-01
Background Splitting describes fragmentation of conscious experience that may occur in various psychiatric disorders. A purpose of this study is to examine relationships between psychological process of splitting and disturbed cognitive and affective functions in schizophrenia and borderline personality disorder (BPD). Methods In the clinical study, we have assessed 30 patients with schizophrenia and 35 patients with BPD. The symptoms of splitting were measured using self-reported Splitting Index (SI). As a measure of semantic memory disorganization we have used verbal fluency test. Other psychopathological symptoms were assessed using Health of the Nation Outcome Scale (HoNOS). Results Main results show that SI is significantly higher in BPD group than in schizophrenia, and on the other hand, verbal fluency is significantly lower in schizophrenia group. Psychopathological symptoms measured by HoNOS are significantly higher in the BPD group than in schizophrenia. Significant relationship was found between verbal fluency and the SI “factor of others” (Spearman r = −0.52, p<0.01) in schizophrenia patients. Conclusions Processes of splitting are different in schizophrenia and BPD. In BPD patients splitting results to mental instability, whereas in schizophrenia the mental fragmentation leads to splitting of associations observed as lower scores of verbal fluency, which in principle is in agreement with Bleuler’s historical concept of splitting in schizophrenia. PMID:24603990
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.
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…
A novel method of the splitting ratio measurement of waveguide coupler using laser beam profiler
NASA Astrophysics Data System (ADS)
Zhang, Yu; Liu, Huilan; Feng, Lishuang; Liu, Jinrong
2016-10-01
At present, the splitting ratio test of the waveguide coupler usually adopts optical fiber coupling test method. The coupling process is complex and the coupling loss is different in two pigtail fibers, what can result in error in the splitting ratio. A new method for testing the splitting ratio of waveguide coupler using laser beam profiler is presented. Laser beam profiler is used to scan the horizontal directional light field in the cross-section of the waveguide. The measurement data are obtained. Data fitting and processing is carried out by data processing program. Finally, two light field curves are gotten, and the splitting ratio of the waveguide coupler is calculated. The feasibility of the new method is verified using fiber coupler. The error using the new method is only 0.68%. The waveguide coupler testing platform is built. The relationship between the measurement range of the splitting ratio and the minimum distances of the waveguide coupler is analyzed. The research provides an effective and convenient method for the test of splitting ratio of waveguide coupler.
Real-time Algorithms for Sparse Neuronal System Identification.
Sheikhattar, Alireza; Babadi, Behtash
2016-08-01
We consider the problem of sparse adaptive neuronal system identification, where the goal is to estimate the sparse time-varying neuronal model parameters in an online fashion from neural spiking observations. We develop two adaptive filters based on greedy estimation techniques and regularized log-likelihood maximization. We apply the proposed algorithms to simulated spiking data as well as experimentally recorded data from the ferret's primary auditory cortex during performance of auditory tasks. Our results reveal significant performance gains achieved by the proposed algorithms in terms of sparse identification and trackability, compared to existing algorithms.
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.
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.
Face split interpretations in sheet metal design
NASA Astrophysics Data System (ADS)
Vitalii, Vorkov; Dewil, Reginald; Mannaerts, Jef; Vandepitte, Dirk; Duflou, Joost R.
2016-10-01
Most of the modern CAD systems have capabilities to work with sheet metal parts. However, the functionality of these modules is limited to modelling, unfolding and delivering project documentation. In some cases the proposed design cannot be manufactured without splitting one or more faces of the part. In the current work, the graph representation of sheet metal parts and corresponding flat patterns are discussed. A splitting procedure is introduced which keeps all existing connections between faces intact. In addition, three interpretations for splitting are presented and recommendations for possible usage are given. The splitting procedure is found to be a convenient option to create feasible flat patterns. In addition, the different splitting interpretations present more flexibility to the designer.
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.
A Search for Miras in M33 Using Sparsely-Sampled Time Series Photometry
NASA Astrophysics Data System (ADS)
Yuan, Wenlong; Macri, Lucas M.; He, Shiyuan; Long, James; Huang, Jianhua
2017-01-01
The Mira Period-Luminosity relations (PLRs) at near- and mid-infrared wavelengths are promising distance indicators, with brighter absolute magnitudes than Cepheids, comparable PLR dispersions and ubiquitous presence in all galaxy types. We developed a semi-parametric Gaussian process periodogram method for sparsely-sampled Mira light curves and applied it to I-band observations of M33. We discovered more than 1800 Miras, which were subsequently classified using machine-learning techniques. We present an overview of the Gaussian process model, the Random Forest classifiers, and the resulting PLRs.
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.
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.
Splitting Methods for Convex Clustering
Chi, Eric C.; Lange, Kenneth
2016-01-01
Clustering is a fundamental problem in many scientific applications. Standard methods such as k-means, Gaussian mixture models, and hierarchical clustering, however, are beset by local minima, which are sometimes drastically suboptimal. Recently introduced convex relaxations of k-means and hierarchical clustering shrink cluster centroids toward one another and ensure a unique global minimizer. In this work we present two splitting methods for solving the convex clustering problem. The first is an instance of the alternating direction method of multipliers (ADMM); the second is an instance of the alternating minimization algorithm (AMA). In contrast to previously considered algorithms, our ADMM and AMA formulations provide simple and unified frameworks for solving the convex clustering problem under the previously studied norms and open the door to potentially novel norms. We demonstrate the performance of our algorithm on both simulated and real data examples. While the differences between the two algorithms appear to be minor on the surface, complexity analysis and numerical experiments show AMA to be significantly more efficient. This article has supplemental materials available online. PMID:27087770
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.
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
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}.
Optical double-image encryption and authentication by sparse representation.
Mohammed, Emad A; Saadon, H L
2016-12-10
An optical double-image encryption and authentication method by sparse representation is proposed. The information from double-image encryption can be integrated into a sparse representation. Unlike the traditional double-image encryption technique, only sparse (partial) data from the encrypted data is adopted for the authentication process. Simulation results demonstrate that the correct authentication results are achieved even with partial information from the encrypted data. The randomly selected sparse encrypted information will be used as an effective key for a security system. Therefore, the proposed method is feasible, effective, and can provide an additional security layer for optical security systems. In addition, the method also achieved the general requirements of storage and transmission due to a high reduction of the encrypted information.
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.
Image denoising via group Sparse representation over learned dictionary
NASA Astrophysics Data System (ADS)
Cheng, Pan; Deng, Chengzhi; Wang, Shengqian; Zhang, Chunfeng
2013-10-01
Images are one of vital ways to get information for us. However, in the practical application, images are often subject to a variety of noise, so that solving the problem of image denoising becomes particularly important. The K-SVD algorithm can improve the denoising effect by sparse coding atoms instead of the traditional method of sparse coding dictionary. In order to further improve the effect of denoising, we propose to extended the K-SVD algorithm via group sparse representation. The key point of this method is dividing the sparse coefficients into groups, so that adjusts the correlation among the elements by controlling the size of the groups. This new approach can improve the local constraints between adjacent atoms, thereby it is very important to increase the correlation between the atoms. The experimental results show that our method has a better effect on image recovery, which is efficient to prevent the block effect and can get smoother images.
Sparse Event Modeling with Hierarchical Bayesian Kernel Methods
2016-01-05
events (and subsequently, their likelihood of occurrence) based on historical evidence of the counts of previous event occurrences. The novel Bayesian...Aug-2014 22-May-2015 Approved for Public Release; Distribution Unlimited Final Report: Sparse Event Modeling with Hierarchical Bayesian Kernel Methods...Sparse Event Modeling with Hierarchical Bayesian Kernel Methods Report Title The research objective of this proposal was to develop a predictive Bayesian
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.
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
Kernelized Elastic Net Regularization: Generalization Bounds, and Sparse Recovery.
Feng, Yunlong; Lv, Shao-Gao; Hang, Hanyuan; Suykens, Johan A K
2016-03-01
Kernelized elastic net regularization (KENReg) is a kernelization of the well-known elastic net regularization (Zou & Hastie, 2005). The kernel in KENReg is not required to be a Mercer kernel since it learns from a kernelized dictionary in the coefficient space. Feng, Yang, Zhao, Lv, and Suykens (2014) showed that KENReg has some nice properties including stability, sparseness, and generalization. In this letter, we continue our study on KENReg by conducting a refined learning theory analysis. This letter makes the following three main contributions. First, we present refined error analysis on the generalization performance of KENReg. The main difficulty of analyzing the generalization error of KENReg lies in characterizing the population version of its empirical target function. We overcome this by introducing a weighted Banach space associated with the elastic net regularization. We are then able to conduct elaborated learning theory analysis and obtain fast convergence rates under proper complexity and regularity assumptions. Second, we study the sparse recovery problem in KENReg with fixed design and show that the kernelization may improve the sparse recovery ability compared to the classical elastic net regularization. Finally, we discuss the interplay among different properties of KENReg that include sparseness, stability, and generalization. We show that the stability of KENReg leads to generalization, and its sparseness confidence can be derived from generalization. Moreover, KENReg is stable and can be simultaneously sparse, which makes it attractive theoretically and practically.
Visual tracking based on extreme learning machine and sparse representation.
Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen
2015-10-22
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.
Sparseness Analysis in the Pretraining of Deep Neural Networks.
Li, Jun; Zhang, Tong; Luo, Wei; Yang, Jian; Yuan, Xiao-Tong; Zhang, Jian
2016-03-31
A major progress in deep multilayer neural networks (DNNs) is the invention of various unsupervised pretraining methods to initialize network parameters which lead to good prediction accuracy. This paper presents the sparseness analysis on the hidden unit in the pretraining process. In particular, we use the L₁-norm to measure sparseness and provide some sufficient conditions for that pretraining leads to sparseness with respect to the popular pretraining models--such as denoising autoencoders (DAEs) and restricted Boltzmann machines (RBMs). Our experimental results demonstrate that when the sufficient conditions are satisfied, the pretraining models lead to sparseness. Our experiments also reveal that when using the sigmoid activation functions, pretraining plays an important sparseness role in DNNs with sigmoid (Dsigm), and when using the rectifier linear unit (ReLU) activation functions, pretraining becomes less effective for DNNs with ReLU (Drelu). Luckily, Drelu can reach a higher recognition accuracy than DNNs with pretraining (DAEs and RBMs), as it can capture the main benefit (such as sparseness-encouraging) of pretraining in Dsigm. However, ReLU is not adapted to the different firing rates in biological neurons, because the firing rate actually changes along with the varying membrane resistances. To address this problem, we further propose a family of rectifier piecewise linear units (RePLUs) to fit the different firing rates. The experimental results show that the performance of RePLU is better than ReLU, and is comparable with those with some pretraining techniques, such as RBMs and DAEs.
Phenomena and Performance of High-Efficiency Split Spectrum Photovoltaics
NASA Astrophysics Data System (ADS)
Downs, Chandler
High-efficiency photovoltaics are one of the most promising technologies for supplying sustainable energy in the near future. These technologies allow for high energy conversion efficiencies and long system lifetimes, which is becoming an increasingly profitable power generation option. One high-efficiency photovoltaic technology gaining increasing attention recent years is that of split-spectrum photovoltaics. This technology divides the incident solar spectrum on the basis of wavelength, directing each portion of the spectrum to a different cell where the light can be utilized most efficiently. In this dissertation, a number of aspects of high-efficiency photovoltaics, most notably split-spectrum photovoltaics, are examined. First, the ideal bandgap placements of the subcells of a split-spectrum photovoltaic system are calculated, specifically determined with an eye towards practical fabrication of the cells. Two viable designs are determined which improve theoretical absolute conversion efficiency by 4-5%. Next, those systems are simulated using the TCAD Sentaurus software package to project conversion efficiencies and determine additional device specifications (doping levels, layer thicknesses, etc.). These cells show comparable conversion efficiencies to high performing, full-spectrum multijunction photovoltaics in fabrication today. In the last section, a theoretical examination of semiconductor performance under high optical concentration is performed, including the prediction and characterization of various phenomena in those devices. This work aims to improve the understanding of the performance of high concentration photovoltaics, most notably split-spectrum photovoltaics. This understanding will aid in the advancement of this technology as a widespread, sustainable energy source for use worldwide, reducing greenhouse emissions and providing cheap, clean energy.
Field by field hybrid upwind splitting methods
NASA Technical Reports Server (NTRS)
Coquel, Frederic; Liou, Meng-Sing
1993-01-01
A new and general approach to upwind splitting is presented. The design principle combines the robustness of flux vector splitting schemes in the capture of nonlinear waves and the accuracy of some flux difference splitting schemes in the resolution of linear waves. The new schemes are derived following a general hybridization technique performed directly at the basic level of the field by field decomposition involved in FDS methods. The scheme does not use a spatial switch to be tuned up according to the local smoothness of the approximate solution.
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.
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.
NASA Astrophysics Data System (ADS)
Apostoleris, Harry; Maragliano, Carlo; Chiesa, Matteo; Stefancich, Marco
2016-09-01
Optical spectrum splitting systems that divide light between independent solar cells of different band gaps have received increasing attention in recent years as an alternative to expensive multijunction cells for high-efficiency PV. Most research, however, has focused on dichroic filters and other photonic structures that are expensive to manufacture. This has the effect of transferring the cost of the system from the PV cells to the optics. As a low-cost spectrum splitting approach we designed a prismatic lens that simultaneously splits and concentrates light and can be fabricated by injection molding. We present experimental results of a two-cell demonstration system, and calculations for low-cost configurations of commercial solar cells, enabled by the removal of lattice-matching requirements.
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.
Split Brain Theory: Implications for Nurse Educators.
ERIC Educational Resources Information Center
de Meneses, Mary
1980-01-01
Discusses incorporating nontraditional concepts of learning in nursing education. Elements explored include the split brain theory, school design, teaching styles, teacher's role, teaching strategies, adding variety to the curriculum, and modular learning. (CT)
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.
The problem of split comets in review
NASA Technical Reports Server (NTRS)
Sekanina, Z.
1982-01-01
Cometary splitting is investigated from the dynamical and physical standpoints. A simple two-parameter model is proposed in which the rate of recession of the fragments is determined by the momentum from outgassing, so that the net differential force is of the same nature as the nongravitational perturbations detected in the motions of unsplit comets; the two parameters of the model are the differential radial acceleration and the time of splitting. It is shown that the model successfully represents the positional observations of nearly all the 21 known split comets. The following candidate triggering mechanisms for cometary splitting are considered: tidal forces, rotation, dust-mantle dumping, and radioactive heating. A model that fits the dynamical data and physical characteristics is presented which suggests that most fragments must be appreciably nonspherical and rapidly precessing.
Split Fingernails: Can They Be Prevented?
... your fingernails dry. Repeated or prolonged contact with water can contribute to split fingernails. Wear cotton-lined rubber gloves when washing dishes, cleaning or using harsh chemicals. Practice good nail hygiene. ...
Irrational beliefs, attitudes about competition, and splitting.
Watson, P J; Morris, R J; Miller, L
2001-03-01
Rational-Emotive Behavior Therapy (REBT) theoretically promotes actualization of both individualistic and social-oriented potentials. In a test of this assumption, the Belief Scale and subscales from the Survey of Personal Beliefs served as measures of what REBT presumes to be pathogenic irrationalities. These measures were correlated with the Hypercompetitive Attitude Scale (HCAS), the Personal Development Competitive Attitude Scale (PDCAS), factors from the Splitting Index, and self-esteem. Results for the HCAS and Self-Splitting supported the REBT claim about individualistic self-actualization. Mostly nonsignificant and a few counterintuitive linkages were observed for irrational beliefs with the PDCAS, Family-Splitting, and Other-Splitting, and these data suggested that REBT may be less successful in capturing the "rationality" of a social-oriented self-actualization.
Optical Characterization of Properties of Split Ring Resonators
NASA Astrophysics Data System (ADS)
de Alba, Roberto; Wang, Kai; Kim, Kyongwan; Bassett, Robert; Trendafilova, Cynthia; Burzo, Andrea; Lyuksyutov, Igor; Sokolov, Alexei
2008-10-01
Negative index materials (NIMs) are artificially made structures with unit cells smaller than the wavelength of incident light. Conceptually, these materials have the potential to revolutionize current technologies -- from allowing us to resolve structures smaller than the wavelength of light, to paving the path towards `invisibility cloaks'. In the past, these structures have been demonstrated to exhibit a negative index of refraction for microwave frequencies. Today, the goal is to develop structures with these properties in the visible wavelength range, and state-of-the-art research has already led to NIMs with resonances near infrared wavelengths. In this work we investigate the influence of different parameters, including size, material, and substrate on the resonant properties of the split ring resonator structures (SRR). In particular, the use of semiconductor substrates could lead to control of the resonant frequencies due to changes in carrier concentration.
Colloidal nanocrystals for photoelectrochemical and photocatalytic water splitting
NASA Astrophysics Data System (ADS)
Gadiyar, Chethana; Loiudice, Anna; Buonsanti, Raffaella
2017-02-01
Colloidal nanocrystals (NCs) are among the most modular and versatile nanomaterial platforms for studying emerging phenomena in different fields thanks to their superb compositional and morphological tunability. A promising, yet challenging, application involves the use of colloidal NCs as light absorbers and electrocatalysts for water splitting. In this review we discuss how the tunability of these materials is ideal to understand the complex phenomena behind storing energy in chemical bonds and to optimize performance through structural and compositional modification. First, we describe the colloidal synthesis method as a means to achieve a high degree of control over single material NCs and NC heterostructures, including examples of the role of the ligands in modulating size and shape. Next, we focus on the use of NCs as light absorbers and catalysts to drive both the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER), together with some of the challenges related to the use of colloidal NCs as model systems and/or technological solution in water splitting. We conclude with a broader prospective on the use of colloidal chemistry for new material discovery.
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.
Conduction band valley splitting in Si
NASA Astrophysics Data System (ADS)
Klimeck, Gerhard; Boykin, T. B.; Eriksson, M.; Friesen, M.; Coppersmith, S. N.; von Allmen, P.; Oyafuso, F.; Lee, S.
2004-03-01
A theory based on localized-orbital approaches is developed to describe the valley splitting observed in silicon nano-structures. The theory is appropriate in the limit of low electron density and relevant for proposed quantum computing architectures. The valley splitting is computed for realistic devices using the quantitative nanoelectronic modeling tool NEMO using the empirical tight binding model sp^3d^5s. The tight binding parameters have been fitted to bulk bandstructure behavior of Si using a genetic algorithm. A 1-D quantum well simulation in NEMO shows the basic features of conduction band valley splitting as a coherent, confinement-induced phenomenon. No additional intervalley scattering parameters are needed. The splitting is in general nonzero even in the absence of electric field. The splitting oscillates as a function of N, the number of layers in the quantum well, with a period that is determined by the location of the valley minimum in the Brillouin zone. The envelope of the splitting decays as N^3. The qualitative physics remain the same irrespective of the details of the quantum well boundaries or the details of the strain treatment in the quantum well.
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.
Lensless wide-field fluorescent imaging on a chip using compressive decoding of sparse objects.
Coskun, Ahmet F; Sencan, Ikbal; Su, Ting-Wei; Ozcan, Aydogan
2010-05-10
We demonstrate the use of a compressive sampling algorithm for on-chip fluorescent imaging of sparse objects over an ultra-large field-of-view (>8 cm(2)) without the need for any lenses or mechanical scanning. In this lensfree imaging technique, fluorescent samples placed on a chip are excited through a prism interface, where the pump light is filtered out by total internal reflection after exciting the entire sample volume. The emitted fluorescent light from the specimen is collected through an on-chip fiber-optic faceplate and is delivered to a wide field-of-view opto-electronic sensor array for lensless recording of fluorescent spots corresponding to the samples. A compressive sampling based optimization algorithm is then used to rapidly reconstruct the sparse distribution of fluorescent sources to achieve approximately 10 microm spatial resolution over the entire active region of the sensor-array, i.e., over an imaging field-of-view of >8 cm(2). Such a wide-field lensless fluorescent imaging platform could especially be significant for high-throughput imaging cytometry, rare cell analysis, as well as for micro-array research.
Load Distribution in Transmissions "Split"
NASA Technical Reports Server (NTRS)
Krantz, Timothy L.; Delgado, Irebert R.
1998-01-01
The transmission system of a helicopter must meet particularly critical requirements. It must transmit engine power to the rotor, at the same time ensuring a typical speed reduction of 60 to 1. It must also be safe, reliable, light, and reach a high level of performance while, at the same time, it must produce few vibrations and little noise. Helicopter transmissions have achieved high-level performances thanks to the combination of analyses, experiments, and the application of practical field experience. However, the new generation of helicopters will require transmission systems that are even safer, lighter, less noisy, and more reliable.
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.
Block-sparse reconstruction and imaging for Lamb wave structural health monitoring.
Levine, Ross M; Michaels, Jennifer E
2014-06-01
A frequently investigated paradigm for monitoring the integrity of plate-like structures is a spatially-distributed array of piezoelectric transducers, with each array element capable of both transmitting and receiving ultrasonic guided waves. This configuration is relatively inexpensive and allows interrogation of defects from multiple directions over a relatively large area. Typically, full sets of pairwise transducer signals are acquired by exciting one transducer at a time in a round-robin fashion. Many algorithms that operate on such data use differential signals that are created by subtracting prerecorded baseline signals, leaving only signal differences introduced by scatterers. Analysis methods such as delay-and-sum imaging operate on these signals to detect and locate point-like defects, but such algorithms have limited performance and suffer when potential scatterers have high directionality or unknown phase-shifting behavior. Signal envelopes are commonly used to mitigate the effects of unknown phase shifts, but this further reduces performance. The blocksparse technique presented here uses a different principle to locate damage: each pixel is assumed to have a corresponding multidimensional linear scattering model, allowing any possible amplitude and phase shift for each transducer pair should a scatterer be present. By assuming that the differential signals are linear combinations of a sparse subset of these models, it is possible to split such signals into location-based components. Results are presented here for three experiments using aluminum and composite plates, each with a different type of scatterer. The scatterers in these images have smaller spot sizes than delay-and-sum imaging, and the images themselves have fewer artifacts. Although a propagation model is required, block-sparse imaging performs well even with a small number of transducers or without access to dispersion curves.
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.
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
2015-04-01
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.
Environment identification in flight using sparse approximation of wing strain
NASA Astrophysics Data System (ADS)
Manohar, Krithika; Brunton, Steven L.; Kutz, J. Nathan
2017-04-01
This paper addresses the problem of identifying different flow environments from sparse data collected by wing strain sensors. Insects regularly perform this feat using a sparse ensemble of noisy strain sensors on their wing. First, we obtain strain data from numerical simulation of a Manduca sexta hawkmoth wing undergoing different flow environments. Our data-driven method learns low-dimensional strain features originating from different aerodynamic environments using proper orthogonal decomposition (POD) modes in the frequency domain, and leverages sparse approximation to classify a set of strain frequency signatures using a dictionary of POD modes. This bio-inspired machine learning architecture for dictionary learning and sparse classification permits fewer costly physical strain sensors while being simultaneously robust to sensor noise. A measurement selection algorithm identifies frequencies that best discriminate the different aerodynamic environments in low-rank POD feature space. In this manner, sparse and noisy wing strain data can be exploited to robustly identify different aerodynamic environments encountered in flight, providing insight into the stereotyped placement of neurons that act as strain sensors on a Manduca sexta hawkmoth wing.
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.
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.
A temporal channel for information in sparse sensory coding
Gupta, Nitin; Stopfer, Mark
2014-01-01
Summary Background Sparse codes are found in nearly every sensory system, but the role of spike timing in sparse sensory coding is unclear. Here we used the olfactory system of awake locusts to test whether the timing of spikes in Kenyon cells, a population of neurons that responds sparsely to odors, carries sensory information to, and influences the responses of, follower neurons. Results We characterized two major classes of direct followers of Kenyon cells. With paired intracellular and field potential recordings made during odor presentations, we found these followers contain information about odor identity in the temporal patterns of their spikes, rather than in the spike rate, the spike phase or the identities of the responsive neurons. Subtly manipulating the relative timing of Kenyon cell spikes with temporally and spatially structured microstimulation reliably altered the response patterns of the followers. Conclusions Our results show that even remarkably sparse spiking responses can provide information through stimulus-specific variations in timing on the order of tens to hundreds of milliseconds, and that these variations can determine the responses of downstream neurons. These results establish the importance of spike timing in a sparse sensory code. PMID:25264257
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
A sparse matrix based full-configuration interaction algorithm.
Rolik, Zoltán; Szabados, Agnes; Surján, Péter R
2008-04-14
We present an algorithm related to the full-configuration interaction (FCI) method that makes complete use of the sparse nature of the coefficient vector representing the many-electron wave function in a determinantal basis. Main achievements of the presented sparse FCI (SFCI) algorithm are (i) development of an iteration procedure that avoids the storage of FCI size vectors; (ii) development of an efficient algorithm to evaluate the effect of the Hamiltonian when both the initial and the product vectors are sparse. As a result of point (i) large disk operations can be skipped which otherwise may be a bottleneck of the procedure. At point (ii) we progress by adopting the implementation of the linear transformation by Olsen et al. [J. Chem Phys. 89, 2185 (1988)] for the sparse case, getting the algorithm applicable to larger systems and faster at the same time. The error of a SFCI calculation depends only on the dropout thresholds for the sparse vectors, and can be tuned by controlling the amount of system memory passed to the procedure. The algorithm permits to perform FCI calculations on single node workstations for systems previously accessible only by supercomputers.
Kurtosis based weighted sparse model with convex optimization technique for bearing fault diagnosis
NASA Astrophysics Data System (ADS)
Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yan, Ruqiang
2016-12-01
The bearing failure, generating harmful vibrations, is one of the most frequent reasons for machine breakdowns. Thus, performing bearing fault diagnosis is an essential procedure to improve the reliability of the mechanical system and reduce its operating expenses. Most of the previous studies focused on rolling bearing fault diagnosis could be categorized into two main families, kurtosis-based filter method and wavelet-based shrinkage method. Although tremendous progresses have been made, their effectiveness suffers from three potential drawbacks: firstly, fault information is often decomposed into proximal frequency bands and results in impulsive feature frequency band splitting (IFFBS) phenomenon, which significantly degrades the performance of capturing the optimal information band; secondly, noise energy spreads throughout all frequency bins and contaminates fault information in the information band, especially under the heavy noisy circumstance; thirdly, wavelet coefficients are shrunk equally to satisfy the sparsity constraints and most of the feature information energy are thus eliminated unreasonably. Therefore, exploiting two pieces of prior information (i.e., one is that the coefficient sequences of fault information in the wavelet basis is sparse, and the other is that the kurtosis of the envelope spectrum could evaluate accurately the information capacity of rolling bearing faults), a novel weighted sparse model and its corresponding framework for bearing fault diagnosis is proposed in this paper, coined KurWSD. KurWSD formulates the prior information into weighted sparse regularization terms and then obtains a nonsmooth convex optimization problem. The alternating direction method of multipliers (ADMM) is sequentially employed to solve this problem and the fault information is extracted through the estimated wavelet coefficients. Compared with state-of-the-art methods, KurWSD overcomes the three drawbacks and utilizes the advantages of both family
12 CFR 7.2023 - Reverse stock splits.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 12 Banks and Banking 1 2014-01-01 2014-01-01 false Reverse stock splits. 7.2023 Section 7.2023... Corporate Practices § 7.2023 Reverse stock splits. (a) Authority to engage in reverse stock splits. A national bank may engage in a reverse stock split if the transaction serves a legitimate corporate...
12 CFR 7.2023 - Reverse stock splits.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 12 Banks and Banking 1 2013-01-01 2013-01-01 false Reverse stock splits. 7.2023 Section 7.2023... Corporate Practices § 7.2023 Reverse stock splits. (a) Authority to engage in reverse stock splits. A national bank may engage in a reverse stock split if the transaction serves a legitimate corporate...
12 CFR 7.2023 - Reverse stock splits.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 12 Banks and Banking 1 2012-01-01 2012-01-01 false Reverse stock splits. 7.2023 Section 7.2023... Corporate Practices § 7.2023 Reverse stock splits. (a) Authority to engage in reverse stock splits. A national bank may engage in a reverse stock split if the transaction serves a legitimate corporate...
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.
Sparse-based multispectral image encryption via ptychography
NASA Astrophysics Data System (ADS)
Rawat, Nitin; Shi, Yishi; Kim, Byoungho; Lee, Byung-Geun
2015-12-01
Recently, we proposed a model of securing a ptychography-based monochromatic image encryption system via the classical Photon-counting imaging (PCI) technique. In this study, we examine a single-channel multispectral sparse-based photon-counting ptychography imaging (SMPI)-based cryptosystem. A ptychography-based cryptosystem creates a complex object wave field, which can be reconstructed by a series of diffraction intensity patterns through an aperture movement. The PCI sensor records only a few complex Bayer patterned samples that have been utilized in the decryption process. Sparse sensing and nonlinear properties of the classical PCI system, together with the scanning probes, enlarge the key space, and such a combination therefore enhances the system's security. We demonstrate that the sparse samples have adequate information for image decryption, as well as information authentication by means of optical correlation.
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.
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.
A note on rank reduction in sparse multivariate regression.
Chen, Kun; Chan, Kung-Sik
A reduced-rank regression with sparse singular value decomposition (RSSVD) approach was proposed by Chen et al. for conducting variable selection in a reduced-rank model. To jointly model the multivariate response, the method efficiently constructs a prespecified number of latent variables as some sparse linear combinations of the predictors. Here, we generalize the method to also perform rank reduction, and enable its usage in reduced-rank vector autoregressive (VAR) modeling to perform automatic rank determination and order selection. We show that in the context of stationary time-series data, the generalized approach correctly identifies both the model rank and the sparse dependence structure between the multivariate response and the predictors, with probability one asymptotically. We demonstrate the efficacy of the proposed method by simulations and analyzing a macro-economical multivariate time series using a reduced-rank VAR model.
Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging
Zhang, Yichun; Shi, Tielin; Su, Lei; Wang, Xiao; Hong, Yuan; Chen, Kepeng; Liao, Guanglan
2016-01-01
Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then we obtain the point spread function, a blur kernel for sparse reconstruction. We reconstruct deblurred images from the oversampled C-scan images based on l1-norm regularization, which can enhance the signal-to-noise ratio and improve the accuracy of micro defect detection. The method is further verified by experimental data. The results demonstrate that the sparse reconstruction is effective for micro defect detection in acoustic micro imaging. PMID:27783040
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.
Combining sparseness and smoothness improves classification accuracy and interpretability.
de Brecht, Matthew; Yamagishi, Noriko
2012-04-02
Sparse logistic regression (SLR) has been shown to be a useful method for decoding high-dimensional fMRI and MEG data by automatically selecting relevant feature dimensions. However, when applied to signals with high spatio-temporal correlations, SLR often over-prunes the feature space, which can result in overfitting and weight vectors that are difficult to interpret. To overcome this problem, we investigate a modification of ℓ₁-normed sparse logistic regression, called smooth sparse logistic regression (SSLR), which has a spatio-temporal "smoothing" prior that encourages weights that are close in time and space to have similar values. This causes the classifier to select spatio-temporally continuous groups of features, whereas SLR classifiers often select a scattered collection of independent features. We applied the method to both simulation data and real MEG data. We found that SSLR consistently increases classification accuracy, and produces weight vectors that are more meaningful from a neuroscientific perspective.
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.
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 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.
Sparse Reconstruction for Micro Defect Detection in Acoustic Micro Imaging.
Zhang, Yichun; Shi, Tielin; Su, Lei; Wang, Xiao; Hong, Yuan; Chen, Kepeng; Liao, Guanglan
2016-10-24
Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then we obtain the point spread function, a blur kernel for sparse reconstruction. We reconstruct deblurred images from the oversampled C-scan images based on l₁-norm regularization, which can enhance the signal-to-noise ratio and improve the accuracy of micro defect detection. The method is further verified by experimental data. The results demonstrate that the sparse reconstruction is effective for micro defect detection in acoustic micro imaging.
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.
Spin splitting in 2D monochalcogenide semiconductors.
Do, Dat T; Mahanti, Subhendra D; Lai, Chih Wei
2015-11-24
We report ab initio calculations of the spin splitting of the uppermost valence band (UVB) and the lowermost conduction band (LCB) in bulk and atomically thin GaS, GaSe, GaTe, and InSe. These layered monochalcogenides appear in four major polytypes depending on the stacking order, except for the monoclinic GaTe. Bulk and few-layer ε-and γ -type, and odd-number β-type GaS, GaSe, and InSe crystals are noncentrosymmetric. The spin splittings of the UVB and the LCB near the Γ-point in the Brillouin zone are finite, but still smaller than those in a zinc-blende semiconductor such as GaAs. On the other hand, the spin splitting is zero in centrosymmetric bulk and even-number few-layer β-type GaS, GaSe, and InSe, owing to the constraint of spatial inversion symmetry. By contrast, GaTe exhibits zero spin splitting because it is centrosymmetric down to a single layer. In these monochalcogenide semiconductors, the separation of the non-degenerate conduction and valence bands from adjacent bands results in the suppression of Elliot-Yafet spin relaxation mechanism. Therefore, the electron- and hole-spin relaxation times in these systems with zero or minimal spin splittings are expected to exceed those in GaAs when the D'yakonov-Perel' spin relaxation mechanism is also suppressed.
Spin splitting in 2D monochalcogenide semiconductors
Do, Dat T.; Mahanti, Subhendra D.; Lai, Chih Wei
2015-01-01
We report ab initio calculations of the spin splitting of the uppermost valence band (UVB) and the lowermost conduction band (LCB) in bulk and atomically thin GaS, GaSe, GaTe, and InSe. These layered monochalcogenides appear in four major polytypes depending on the stacking order, except for the monoclinic GaTe. Bulk and few-layer ε-and γ -type, and odd-number β-type GaS, GaSe, and InSe crystals are noncentrosymmetric. The spin splittings of the UVB and the LCB near the Γ-point in the Brillouin zone are finite, but still smaller than those in a zinc-blende semiconductor such as GaAs. On the other hand, the spin splitting is zero in centrosymmetric bulk and even-number few-layer β-type GaS, GaSe, and InSe, owing to the constraint of spatial inversion symmetry. By contrast, GaTe exhibits zero spin splitting because it is centrosymmetric down to a single layer. In these monochalcogenide semiconductors, the separation of the non-degenerate conduction and valence bands from adjacent bands results in the suppression of Elliot-Yafet spin relaxation mechanism. Therefore, the electron- and hole-spin relaxation times in these systems with zero or minimal spin splittings are expected to exceed those in GaAs when the D’yakonov-Perel’ spin relaxation mechanism is also suppressed. PMID:26596907
Technical Skills Required in Split Liver Transplantation.
Liu, Huanqiu; Li, Ruijun; Fu, Jinling; He, Qianyan; Li, Ji
2016-07-01
The number of liver grafts obtained from a cadaver can be greatly increased with the application of split liver transplantation. In the last 10 years, pediatric waiting list mortality has been reduced significantly with the use of this form of liver transplantation, which has 2 major forms. In its most commonly used form, the liver can be transplanted into 1 adult and 1 child by splitting it into a right extended and a left lateral graft. For adult and pediatric recipients, the results of this procedure are comparable to those of whole-organ techniques. In another form, 2 hemi-grafts are obtained by splitting the liver, which can be transplanted into a medium-sized adult (the right side) and a large child/small adult (the left side). The adult liver graft pool is expanded through the process of full right/full left splitting; but it is also a critical technique when one considers the knowledge required of the potential anatomic variations and the high technical skill level needed. In this review, we provide some basic insights into the technical and anatomical aspects of these 2 forms of split liver transplantation and present an updated summary of both forms.
Spin splitting in 2D monochalcogenide semiconductors
NASA Astrophysics Data System (ADS)
Do, Dat T.; Mahanti, Subhendra D.; Lai, Chih Wei
2015-11-01
We report ab initio calculations of the spin splitting of the uppermost valence band (UVB) and the lowermost conduction band (LCB) in bulk and atomically thin GaS, GaSe, GaTe, and InSe. These layered monochalcogenides appear in four major polytypes depending on the stacking order, except for the monoclinic GaTe. Bulk and few-layer ε-and γ -type, and odd-number β-type GaS, GaSe, and InSe crystals are noncentrosymmetric. The spin splittings of the UVB and the LCB near the Γ-point in the Brillouin zone are finite, but still smaller than those in a zinc-blende semiconductor such as GaAs. On the other hand, the spin splitting is zero in centrosymmetric bulk and even-number few-layer β-type GaS, GaSe, and InSe, owing to the constraint of spatial inversion symmetry. By contrast, GaTe exhibits zero spin splitting because it is centrosymmetric down to a single layer. In these monochalcogenide semiconductors, the separation of the non-degenerate conduction and valence bands from adjacent bands results in the suppression of Elliot-Yafet spin relaxation mechanism. Therefore, the electron- and hole-spin relaxation times in these systems with zero or minimal spin splittings are expected to exceed those in GaAs when the D’yakonov-Perel’ spin relaxation mechanism is also suppressed.
Conditions for a split diffusion flame
Hertzberg, J.R.
1997-05-01
An unusual phenomenon has been observed in a methane jet diffusion flame subjected to axial acoustic forcing. At specific excitation frequencies and amplitudes, the driven flame splits into a central jet and one or two side jets. The splitting is accompanied by a partial detachment of the flame from the nozzle exit, a shortening of the flame by a factor of 2, and a change from the common yellow color of soot radiation to a clear blue flame. Such a phenomenon may be useful for the control of soot production or product species. The splitting is intermittent in time, bifurcating between the split flame and an ordinary single jet diffusion flame. The experiment consists of an unconfined axisymmetric methane jet formed by a short length of 0.4 cm diameter pipe. The pipe is connected to a large plenum surrounding a bass reflex loudspeaker enclosure that provides the excitation. Conditions producing split and bifurcated flames are presented. The drive frequencies required to cause bifurcation correspond to the first two peaks in the system`s frequency response curve. Bifurcating behavior was observed at a wide range of flow rates, ranging from very small flames of Reynolds number 240 up to turbulent lift-off, at Re = 1,000, based on the inner pipe diameter. It was not sensitive to nozzle length, but the details of the nozzle tip, such as orifice or pipe geometry, can affect the frequency range.
Sparse grid techniques for particle-in-cell schemes
NASA Astrophysics Data System (ADS)
Ricketson, L. F.; Cerfon, A. J.
2017-02-01
We propose the use of sparse grids to accelerate particle-in-cell (PIC) schemes. By using the so-called ‘combination technique’ from the sparse grids literature, we are able to dramatically increase the size of the spatial cells in multi-dimensional PIC schemes while paying only a slight penalty in grid-based error. The resulting increase in cell size allows us to reduce the statistical noise in the simulation without increasing total particle number. We present initial proof-of-principle results from test cases in two and three dimensions that demonstrate the new scheme’s efficiency, both in terms of computation time and memory usage.
High Angular Resolution Microwave Sensing with Large, Sparse, Random Arrays.
1982-12-01
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Moving target detection for frequency agility radar by sparse reconstruction.
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.
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.
Communication requirements of sparse Cholesky factorization with nested dissection ordering
NASA Technical Reports Server (NTRS)
Naik, Vijay K.; Patrick, Merrell L.
1989-01-01
Load distribution schemes for minimizing the communication requirements of the Cholesky factorization of dense and sparse, symmetric, positive definite matrices on multiprocessor systems are presented. The total data traffic in factoring an n x n sparse symmetric positive definite matrix representing an n-vertex regular two-dimensional grid graph using n exp alpha, alpha not greater than 1, processors are shown to be O(n exp 1 + alpha/2). It is O(n), when n exp alpha, alpha not smaller than 1, processors are used. Under the conditions of uniform load distribution, these results are shown to be asymptotically optimal.
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.
Sparse coding based feature representation method for remote sensing images
NASA Astrophysics Data System (ADS)
Oguslu, Ender
In this dissertation, we study sparse coding based feature representation method for the classification of multispectral and hyperspectral images (HSI). The existing feature representation systems based on the sparse signal model are computationally expensive, requiring to solve a convex optimization problem to learn a dictionary. A sparse coding feature representation framework for the classification of HSI is presented that alleviates the complexity of sparse coding through sub-band construction, dictionary learning, and encoding steps. In the framework, we construct the dictionary based upon the extracted sub-bands from the spectral representation of a pixel. In the encoding step, we utilize a soft threshold function to obtain sparse feature representations for HSI. Experimental results showed that a randomly selected dictionary could be as effective as a dictionary learned from optimization. The new representation usually has a very high dimensionality requiring a lot of computational resources. In addition, the spatial information of the HSI data has not been included in the representation. Thus, we modify the framework by incorporating the spatial information of the HSI pixels and reducing the dimension of the new sparse representations. The enhanced model, called sparse coding based dense feature representation (SC-DFR), is integrated with a linear support vector machine (SVM) and a composite kernels SVM (CKSVM) classifiers to discriminate different types of land cover. We evaluated the proposed algorithm on three well known HSI datasets and compared our method to four recently developed classification methods: SVM, CKSVM, simultaneous orthogonal matching pursuit (SOMP) and image fusion and recursive filtering (IFRF). The results from the experiments showed that the proposed method can achieve better overall and average classification accuracies with a much more compact representation leading to more efficient sparse models for HSI classification. To further
An evaluation of GPU acceleration for sparse reconstruction
NASA Astrophysics Data System (ADS)
Braun, Thomas R.
2010-04-01
Image processing applications typically parallelize well. This gives a developer interested in data throughput several different implementation options, including multiprocessor machines, general purpose computation on the graphics processor, and custom gate-array designs. Herein, we will investigate these first two options for dictionary learning and sparse reconstruction, specifically focusing on the K-SVD algorithm for dictionary learning and the Batch Orthogonal Matching Pursuit for sparse reconstruction. These methods have been shown to provide state of the art results for image denoising, classification, and object recognition. We'll explore the GPU implementation and show that GPUs are not significantly better or worse than CPUs for this application.
Multiscale Sparse Image Representation with Learned Dictionaries (PREPRINT)
2007-01-01
age processing, e.g., image denoising [5]. In [1] the K- SVD is proposed for learning a single-scale dic- tionary for sparse representation of image...performance we obtain. 2. THE SINGLE-SCALE K- SVD DENOISING ALGORITHM In this section, we briefly review the main ideas of the K- SVD frame- work for sparse...weighted average: x̂ = “ λI + X ij R T ijRij ”−1“ λy + X ij R T ijD̂α̂ij ” . (4) Fig. 1. The single-scale K- SVD -based image denoising algorithm. Fig
Accelerated nonlinear multichannel ultrasonic tomographic imaging using target sparseness.
Chengdong Dong; Yuanwei Jin; Enyue Lu
2014-03-01
This paper presents an accelerated iterative Landweber method for nonlinear ultrasonic tomographic imaging in a multiple-input multiple-output (MIMO) configuration under a sparsity constraint on the image. The proposed method introduces the emerging MIMO signal processing techniques and target sparseness constraints in the traditional computational imaging field, thus significantly improves the speed of image reconstruction compared with the conventional imaging method while producing high quality images. Using numerical examples, we demonstrate that incorporating prior knowledge about the imaging field such as target sparseness accelerates significantly the convergence of the iterative imaging method, which provides considerable benefits to real-time tomographic imaging applications.
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.
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.
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.
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
NASA Astrophysics Data System (ADS)
Vorndran, Shelby D.; Wu, Yuechen; Ayala, Silvana; Kostuk, Raymond K.
2015-09-01
Concentrating and spectrum splitting photovoltaic (PV) modules have a limited acceptance angle and thus suffer from optical loss under off-axis illumination. This loss manifests itself as a substantial reduction in energy yield in locations where a significant portion of insulation is diffuse. In this work, a spectrum splitting PV system is designed to efficiently collect and convert light in a range of illumination conditions. The system uses a holographic lens to concentrate shortwavelength light onto a smaller, more expensive indium gallium phosphide (InGaP) PV cell. The high efficiency PV cell near the axis is surrounded with silicon (Si), a less expensive material that collects a broader portion of the solar spectrum. Under direct illumination, the device achieves increased conversion efficiency from spectrum splitting. Under diffuse illumination, the device collects light with efficiency comparable to a flat-panel Si module. Design of the holographic lens is discussed. Optical efficiency and power output of the module under a range of illumination conditions from direct to diffuse are simulated with non-sequential raytracing software. Using direct and diffuse Typical Metrological Year (TMY3) irradiance measurements, annual energy yield of the module is calculated for several installation sites. Energy yield of the spectrum splitting module is compared to that of a full flat-panel Si reference module.
Spatial Light Amplifier Modulators
NASA Technical Reports Server (NTRS)
Eng, Sverre T.; Olsson, N. Anders
1992-01-01
Spatial light amplifier modulators (SLAM's) are conceptual devices that effect two-dimensional spatial modulation in optical computing and communication systems. Unlike current spatial light modulators, these provide gain. Optical processors incorporating SLAM's designed to operate in reflection or transmission mode. Each element of planar SLAM array is optical amplifier - surface-emitting diode laser. Array addressed electrically with ac modulating signals superimposed on dc bias currents supplied to lasers. SLAM device provides both desired modulation and enough optical gain to enable splitting of output signal into many optical fibers without excessive loss of power.
Solar Water Splitting and Nitrogen Fixation with Layered Bismuth Oxyhalides.
Li, Jie; Li, Hao; Zhan, Guangming; Zhang, Lizhi
2017-01-17
their migration from the bulk to the surface along the different directions, thus enabling more electrons to reach the surface for water splitting and nitrogen fixation. Simultaneously, their oxygen termination feature and the strain differences between interlayers and intralayers render the easy generation of surface oxygen vacancies (OVs) that afford Lewis-base and unsaturated-unsaturated sites for nitrogen activation. With these rationales as the guideline, we can obtain striking visible-light hydrogen- and ammonia-evolving rates without using any noble-metal cocatalysts. Then we show how to utilize IEF and OV based strategies to improve the solar water splitting and nitrogen fixation performances of bismuth oxyhalide photocatalysts. Finally, we highlight the challenges remaining in using bismuth oxyhalides for solar hydrogen and ammonia syntheses, and the prospect of further development of this research field. We believe that our mechanistic insights could serve as a blueprint for the design of more efficient solar water splitting and nitrogen fixation systems, and layered bismuth oxyhalides might open up new photocatalyst paradigm for such two solar chemical syntheses.
Resonance splitting in gyrotropic ring resonators.
Jalas, Dirk; Petrov, Alexander; Krause, Michael; Hampe, Jan; Eich, Manfred
2010-10-15
We present the theoretical concept of an optical isolator based on resonance splitting in a silicon ring resonator covered with a magneto-optical polymer cladding. For this task, a perturbation method is derived for the modes in the cylindrical coordinate system. A polymer magneto-optical cladding causing a 0.01 amplitude of the off-diagonal element of the dielectric tensor is assumed. It is shown that the derived resonance splitting of the clockwise and counterclockwise modes increases for smaller ring radii. For the ring with a radius of approximately 1.5μm, a 29GHz splitting is demonstrated. An integrated optical isolator with a 10μm geometrical footprint is proposed based on a critically coupled ring resonator.
Notes on the genesis of pathological splitting.
Ross, J M; Dunn, P B
1980-01-01
In this preliminary paper, we have concentrated on the reverberating system that may develop as parents respond to the rapprochement toddler's ambitendent communications of split objects and to some of the ways in which these interactions may become reactivated later in borderline transference phenomena. We have hypothesized that such splits in mental content underlie communication of a fixed, binary and dualistic nature, such as communication that characterizes the so-called double bind. We have further suggested that the double bind, when understood in the context of object relations, usefully highlights the process whereby parent and then therapist become unwitting participants in the toddler's or borderline's world of split-off part objects. Finally, we have touched on certain therapeutic implications, emphasizing the developmental impact of interpreting borderline transference phenomena.
Multiple Spectral Splits of Supernova Neutrinos
Dasgupta, Basudeb; Raffelt, Georg G.; Dighe, Amol; Smirnov, Alexei Yu.
2009-07-31
Collective oscillations of supernova neutrinos swap the spectra f{sub n}u{sub e}(E) and f{sub n}u{sub e}(E) with those of another flavor in certain energy intervals bounded by sharp spectral splits. This phenomenon is far more general than previously appreciated: typically one finds one or more swaps and accompanying splits in the nu and nu channels for both inverted and normal neutrino mass hierarchies. Depending on an instability condition, swaps develop around spectral crossings (energies where f{sub n}u{sub e}=f{sub n}u{sub x}, f{sub n}u{sub e}=f{sub n}u{sub x} as well as E->infinity where all fluxes vanish), and the widths of swaps are determined by the spectra and fluxes. Washout by multiangle decoherence varies across the spectrum and splits can survive as sharp spectral features.
Multiple spectral splits of supernova neutrinos.
Dasgupta, Basudeb; Dighe, Amol; Raffelt, Georg G; Smirnov, Alexei Yu
2009-07-31
Collective oscillations of supernova neutrinos swap the spectra f(nu(e))(E) and f(nu[over ](e))(E) with those of another flavor in certain energy intervals bounded by sharp spectral splits. This phenomenon is far more general than previously appreciated: typically one finds one or more swaps and accompanying splits in the nu and nu[over ] channels for both inverted and normal neutrino mass hierarchies. Depending on an instability condition, swaps develop around spectral crossings (energies where f(nu(e))=f(nu(x)), f(nu[over ](e))=f(nu[over ](x)) as well as E-->infinity where all fluxes vanish), and the widths of swaps are determined by the spectra and fluxes. Washout by multiangle decoherence varies across the spectrum and splits can survive as sharp spectral features.
Rabi splitting enhancement in semiconductor microcavities
NASA Astrophysics Data System (ADS)
Dickerson, James Henry, II
The physics of the two-level atom has been the basis of research in atomic physics for much of the past several decades. One of the great successes of semiconductor physics has been its capability to mimic the phenomena of other physical systems. Many of the discoveries in atomic physics have prompted studies of the coupling between two-level atom-like structures and photonic system in semiconductor physics. Much of that work has investigated the optics of the energy exchange between atom-like systems and the electromagnetic field mode of the enclosing cavity. Since many applications of microcavities are governed by the control of the spontaneous emission from the structure, command of the emission relies on control of the coupling between the photonic and the excitonic modes of the system. When the energies of the interacting microcavity states are in resonance, the resulting degeneracy yields an energy split between the coincident modes. This energy split produces two branches of the resonant mixed states, which are called polaritons. The energy separation between the mixed state branches is called the vacuum Rabi splitting, Delta. The magnitude of the Rabi splitting is indicative of the coupling strength of the polariton modes. One of the major pursuits of this field has been to augment the control of the coupling strength between the cavity polariton modes. Comprehensive control over the polariton states, be it the modulation of the polariton energies or the suppression of one of the modes, is a key component in the development of microcavity devices. The goal of my thesis research was to discover a simple means to achieve control over the coupling between the photonic and excitonic modes of a microcavity. This entailed the parametric tuning of the Rabi splitting between the coupled modes of the microcavity. Furthermore, we hoped to attain the maximum possible Rabi splitting observed in GaAs/AlxGa1- xAs microcavities with quantum oscillators located only within
The splitting of Comet Halley 1986
NASA Astrophysics Data System (ADS)
Chen, Dao-Han; Zheng, Jia-Quing; Liu, Zong-Li; Yan, Lin-Shan; Lui, Lin-Zhong; Zhou, Xing-Hai; Wu, Zhi-Xian; Gilmore, A. C.
1987-09-01
Nine photographs taken on 25 Mar., 1986 show that the nucleus of Comet Halley split into 2 widely separated nuclei. The separated projected distance on the plane of the sky is 5000 km. The principal nucleus and the secondary nucleus exhibit their own comas. The prominant jet ejected from the companion curves up to a height of several thousand kilometers and the secondary nucleus must fade out of sight within only a few days. In combination with the results of photoelectric observations it seems that this event of splitting coincides with an outburst. Photographs were digitized, and the image enhancement is described.
Fermion localization on a split brane
Chumbes, A. E. R.; Vasquez, A. E. O.; Hott, M. B.
2011-05-15
In this work we analyze the localization of fermions on a brane embedded in five-dimensional, warped and nonwarped, space-time. In both cases we use the same nonlinear theoretical model with a nonpolynomial potential featuring a self-interacting scalar field whose minimum energy solution is a soliton (a kink) which can be continuously deformed into a two-kink. Thus a single brane splits into two branes. The behavior of spin 1/2 fermions wave functions on the split brane depends on the coupling of fermions to the scalar field and on the geometry of the space-time.
Parallel programming in Split-C
Culler, D.E.; Dusseau, A.; Goldstein, S.C.; Krishnamurthy, A.; Lumetta, S.; Eicken, T. von; Yelick, K.
1993-12-31
The authors introduce the Split-C language, a parallel extension of C intended for high performance programming on distributed memory multiprocessors, and demonstrate the use of the language in optimizing parallel programs. Split-C provides a global address space with a clear concept of locality and unusual assignment operators. These are used as tools to reduce the frequency and cost of remote access. The language allows a mixture of shared memory, message passing, and data parallel programming styles while providing efficient access to the underlying machine. They demonstrate the basic language concepts using regular and irregular parallel programs and give performance results for various stages of program optimization.