ENVIRONMENTAL ASSESSMENT OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS
This report summarizes laboratory-scale, pilot-scale, and field performance data on BCD (Base Catalyzed Decomposition) and technology, collected to date by various governmental, academic, and private organizations.
ENVIRONMENTAL ASSESSMENT OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS
This report summarizes laboratory-scale, pilot-scale, and field performance data on BCD (Base Catalyzed Decomposition) and technology, collected to date by various governmental, academic, and private organizations.
MEMS-Based Satellite Micropropulsion Via Catalyzed Hydrogen Peroxide Decomposition
NASA Technical Reports Server (NTRS)
Hitt, Darren L.; Zakrzwski, Charles M.; Thomas, Michael A.; Bauer, Frank H. (Technical Monitor)
2001-01-01
Micro-electromechanical systems (MEMS) techniques offer great potential in satisfying the mission requirements for the next generation of "micro-scale" satellites being designed by NASA and Department of Defense agencies. More commonly referred to as "nanosats", these miniature satellites feature masses in the range of 10-100 kg and therefore have unique propulsion requirements. The propulsion systems must be capable of providing extremely low levels of thrust and impulse while also satisfying stringent demands on size, mass, power consumption and cost. We begin with an overview of micropropulsion requirements and some current MEMS-based strategies being developed to meet these needs. The remainder of the article focuses the progress being made at NASA Goddard Space Flight Center towards the development of a prototype monopropellant MEMS thruster which uses the catalyzed chemical decomposition of high concentration hydrogen peroxide as a propulsion mechanism. The products of decomposition are delivered to a micro-scale converging/diverging supersonic nozzle which produces the thrust vector; the targeted thrust level approximately 500 N with a specific impulse of 140-180 seconds. Macro-scale hydrogen peroxide thrusters have been used for satellite propulsion for decades; however, the implementation of traditional thruster designs on a MEMS scale has uncovered new challenges in fabrication, materials compatibility, and combustion and hydrodynamic modeling. A summary of the achievements of the project to date is given, as is a discussion of remaining challenges and future prospects.
Chemical dehalogenation treatment: Base-catalyzed decomposition process (BCDP). Tech data sheet
Not Available
1992-07-01
The Base-Catalyzed Decomposition Process (BCDP) is an efficient, relatively inexpensive treatment process for polychlorinated biphenyls (PCBs). It is also effective on other halogenated contaminants such as insecticides, herbicides, pentachlorophenol (PCP), lindane, and chlorinated dibenzodioxins and furans. The heart of BCDP is the rotary reactor in which most of the decomposition takes place. The contaminated soil is first screened, processed with a crusher and pug mill, and stockpiled. Next, in the main treatment step, this stockpile is mixed with sodium bicarbonate (in the amount of 10% of the weight of the stockpile) and heated for about one hour at 630 F in the rotary reactor. Most (about 60% to 90%) of the PCBs in the soil are decomposed in this step. The remainder are volatilized, captured, and decomposed.
Schmidt, A.J.; Freeman, H.D.; Brown, M.D.; Zacher, A.H.; Neuenschwander, G.N.; Wilcox, W.A.; Gano, S.R.; Kim, B.C.; Gavaskar, A.R.
1996-02-01
Base Catalyzed Decomposition (BCD) is a chemical dehalogenation process designed for treating soils and other substrate contaminated with polychlorinated biphenyls (PCB), pesticides, dioxins, furans, and other hazardous organic substances. PCBs are heavy organic liquids once widely used in industry as lubricants, heat transfer oils, and transformer dielectric fluids. In 1976, production was banned when PCBs were recognized as carcinogenic substances. It was estimated that significant quantities (one billion tons) of U.S. soils, including areas on U.S. military bases outside the country, were contaminated by PCB leaks and spills, and cleanup activities began. The BCD technology was developed in response to these activities. This report details the evolution of the process, from inception to deployment in Guam, and describes the process and system components provided to the Navy to meet the remediation requirements. The report is divided into several sections to cover the range of development and demonstration activities. Section 2.0 gives an overview of the project history. Section 3.0 describes the process chemistry and remediation steps involved. Section 4.0 provides a detailed description of each component and specific development activities. Section 5.0 details the testing and deployment operations and provides the results of the individual demonstration campaigns. Section 6.0 gives an economic assessment of the process. Section 7.0 presents the conclusions and recommendations form this project. The appendices contain equipment and instrument lists, equipment drawings, and detailed run and analytical data.
Hu, Xintao; Zhu, Jianxin; Ding, Qiong
2011-07-15
Remediation action is critical for the management of polychlorinated biphenyl (PCB) contaminated sites. Dozens of remediation technologies developed internationally could be divided in two general categories incineration and non-incineration. In this paper, life cycle assessment (LCA) was carried out to study the environmental impacts of these two kinds of remediation technologies in selected PCB contaminated sites, where Infrared High Temperature Incineration (IHTI) and Base Catalyzed Decomposition (BCD) were selected as representatives of incineration and non-incineration. A combined midpoint/damage approach was adopted by using SimaPro 7.2 and IMPACTA2002+ to assess the human toxicity, ecotoxicity, climate change impact, and resource consumption from the five subsystems of IHTI and BCD technologies, respectively. It was found that the major environmental impacts through the whole lifecycle arose from energy consumption in both IHTI and BCD processes. For IHTI, primary and secondary combustion subsystem contributes more than 50% of midpoint impacts concerning with carcinogens, respiratory inorganics, respiratory organics, terrestrial ecotoxity, terrestrial acidification/eutrophication and global warming. In BCD process, the rotary kiln reactor subsystem presents the highest contribution to almost all the midpoint impacts including global warming, non-renewable energy, non-carcinogens, terrestrial ecotoxity and respiratory inorganics. In the view of midpoint impacts, the characterization values for global warming from IHTI and BCD were about 432.35 and 38.5 kg CO(2)-eq per ton PCB-containing soils, respectively. LCA results showed that the single score of BCD environmental impact was 1468.97 Pt while IHTI's score is 2785.15 Pt, which indicates BCD potentially has a lower environmental impact than IHTI technology in the PCB contaminated soil remediation process.
EVALUATION OF THE FULL-SCALE BASE CATALYZED DECOMPOSITION PROCESS (BCDP) UNIT LOCATED IN GUAM
This report summarizes performance data collected in February 1997 on the removal of polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs) from soil fed to a first-stage rotary kiln reactor of the Base Catalyzed Dec...
EVALUATION OF THE FULL-SCALE BASE CATALYZED DECOMPOSITION PROCESS (BCDP) UNIT LOCATED IN GUAM
This report summarizes performance data collected in February 1997 on the removal of polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs) from soil fed to a first-stage rotary kiln reactor of the Base Catalyzed Dec...
Organic acids tunably catalyze carbonic acid decomposition.
Kumar, Manoj; Busch, Daryle H; Subramaniam, Bala; Thompson, Ward H
2014-07-10
Density functional theory calculations predict that the gas-phase decomposition of carbonic acid, a high-energy, 1,3-hydrogen atom transfer reaction, can be catalyzed by a monocarboxylic acid or a dicarboxylic acid, including carbonic acid itself. Carboxylic acids are found to be more effective catalysts than water. Among the carboxylic acids, the monocarboxylic acids outperform the dicarboxylic ones wherein the presence of an intramolecular hydrogen bond hampers the hydrogen transfer. Further, the calculations reveal a direct correlation between the catalytic activity of a monocarboxylic acid and its pKa, in contrast to prior assumptions about carboxylic-acid-catalyzed hydrogen-transfer reactions. The catalytic efficacy of a dicarboxylic acid, on the other hand, is significantly affected by the strength of an intramolecular hydrogen bond. Transition-state theory estimates indicate that effective rate constants for the acid-catalyzed decomposition are four orders-of-magnitude larger than those for the water-catalyzed reaction. These results offer new insights into the determinants of general acid catalysis with potentially broad implications.
Kinetic modeling of Pt-catalyzed glycolaldehyde decomposition to syngas.
Salciccioli, Michael; Vlachos, Dionisios G
2012-05-10
Fundamental knowledge of the elementary reaction mechanisms involved in oxygenate decomposition on transition metal catalysts can facilitate the optimization of future catalyst and reactor systems for biomass upgrade to fuels and chemicals. Pt-catalyzed decomposition of glycolaldehyde, as the smallest oxygenate with alcohol and aldehyde functionality, was studied via a DFT-based microkinetic model. It was found that two decomposition pathways exist. Under conditions of low hydrogen surface coverage, the initial C-H bond breaking reaction to HOCH(2)CO* is prevalent, while under conditions of high hydrogen coverage, the rather unexpected O-H bond forming reaction to HOCH(2)CHOH* is more active (subsequent decomposition is energetically favorable from HOCH(2)CHOH*). Our results indicate the possibility that (de)hydrogenation chemistry is rate-controlling in many small polyoxygenate biomass derivatives, and suitable catalysts are needed. Finally, DFT was used to understand the increased decomposition activity observed on the surface segregated Ni-Pt-Pt bimetallic catalyst. It was found that the initial O-H bond breaking of glycolaldehyde to OCH(2)CHO* has an activation barrier of just 0.21 eV. This barrier is lower than that of any glycolaldehyde consuming reaction on Pt. These computational predictions are in qualitative agreement with experimental results.
Mechanism of Cu(II)-catalyzed monochloramine decomposition in aqueous solution.
Fu, Jun; Qu, Jiuhui; Liu, Ruiping; Qiang, Zhimin; Zhao, Xu; Liu, Huijuan
2009-06-15
The decomposition of monochloramine, which is commonly used as a secondary disinfectant at water treatment plants to reduce the formation of disinfection byproducts, always occurs in water and can be accelerated by certain catalytic substances. This work was to investigate the mechanism of monochloramine decomposition catalyzed by Cu(II) in aqueous solution. Ultraviolet (UV) spectral results showed that either Cu(II) addition or pH decrease would significantly promote the transformation of monochloramine to dichloramine. A copper intermediate, Cu(I), was extracted from the NH(2)Cl-Cu(II) solution by solid-phase extraction and identified by X-ray photoelectron spectroscopy (XPS). Electron spin resonance (ESR) results showed that hydroxyl radical (.OH) and amidogen radical (.NH(2)) were generated in the reaction between monochloramine and Cu(II). These radical intermediates also contributed to monochloramine decomposition. Based on the experimental results, the reaction mechanism for Cu(II)-catalyzed monochloramine decomposition was proposed which consisted of two pathways: 1) direct catalysis in which Cu(II) acts as a Lewis acid to accelerate monochloramine decomposition to dichloramine (major pathway); and 2) indirect catalysis in which the active radical intermediates (.OH and .NH(2)) react with monochloramine and lead to its decomposition (minor pathway).
Decomposition of peracetic acid catalyzed by vanadium complexes
Makarov, A.P.; Gekhman, A.E.; Moiseev, I.I.; Polotryuk, O.Y.
1986-02-01
This paper studies the decomposition of peracetic acid (AcOOH) in acetic acid (AcOH) catalyzed by vanadium complexes. It is shown that peractic acid in acetic acid solutions of ammonium anadate decomposes with the predominant formation of 0/sub 2/ and small amounts of CO/sub 2/, the yield of which increases with increasing temperature and peracetic acid concentration. Both reactions proceed without the formation of free radicals in amounts detectable by ESR spectroscopy. The rate of oxygen release under conditions in which the formation of CO/sub 2/ is insignificant obeys a kinetic equation indicating the intermediate formation of a complex between V/sup 5 +/ ions and peracetic acid and the slow conversion of this complex into the observed products.
The platinum-catalyzed decomposition of methanol: A deceptive demonstration
Coffing, D.L.; Wile, J.L. )
1993-07-01
The platinum-catalyzed gas-phase decomposition of methanol can be used for classroom demonstration in an exciting, interesting fashion. The platinum catalysts, after being heated until it glows, can be made to continue glowing for hours by suspending it over the methanol. This demonstration is useful in a classroom setting for several reasons. First it is more complicated than it appears initially, involving a reaction that is not immediately obvious and is, therefore, more challenging for students to understand. Second, the platinum illustrates the phenomenon of exothermic reactions in a distinctive and memorable way. Because the platinum foil has to be heated before the reactions will proceed, this demonstration also is a perfect example of the temperature dependence of [Delta]G in determining the spontaneity of a reaction. Finally, this demonstration can be used to explain the mutual interaction of two reactions. Because an explanation of this demonstration requires the use of many chemical concepts, it is an ideal activity for stimulating synthesis among students near the end of the course.
Kinetics of Platinum-Catalyzed Decomposition of Hydrogen Peroxide
NASA Astrophysics Data System (ADS)
Vetter, Tiffany A.; Colombo, D. Philip, Jr.
2003-07-01
CIBA Vision Corporation markets a contact lens cleaning system that consists of an AOSEPT disinfectant solution and an AOSEPT lens cup. The disinfectant is a buffered 3.0% m/v hydrogen peroxide solution and the cup includes a platinum-coated AOSEPT disc. The hydrogen peroxide disinfects by killing bacteria, fungi, and viruses found on the contact lenses. Because the concentration of hydrogen peroxide needed to disinfect is irritating to eyes, the hydrogen peroxide needs to be neutralized, or decomposed, before the contact lenses can be used again. A general chemistry experiment is described where the kinetics of the catalyzed decomposition of the hydrogen peroxide are studied by measuring the amount of oxygen generated as a function of time. The order of the reaction with respect to the hydrogen peroxide, the rate constant, and the energy of activation are determined. The integrated rate law is used to determine the time required to decompose the hydrogen peroxide to a concentration that is safe for eyes.
Oxidative decomposition of formaldehyde catalyzed by a bituminous coal
Haim Cohen; Uri Green
2009-05-15
It has been observed that molecular hydrogen is formed during long-term storage of bituminous coals via oxidative decomposition of formaldehyde by coal surface peroxides. This study has investigated the effects of coal quantity, temperature, and water content on the molecular hydrogen formation with a typical American coal (Pittsburgh No. 6). The results indicate that the coal's surface serves as a catalyst in the formation processes of molecular hydrogen. Furthermore, the results also indicate that low temperature emission of molecular hydrogen may possibly be the cause of unexplained explosions in confined spaces containing bituminous coals, for example, underground mines or ship holds. 20 refs., 4 figs., 6 tabs.
Cytochrome bd from Escherichia coli catalyzes peroxynitrite decomposition.
Borisov, Vitaliy B; Forte, Elena; Siletsky, Sergey A; Sarti, Paolo; Giuffrè, Alessandro
2015-02-01
Cytochrome bd is a prokaryotic respiratory quinol oxidase phylogenetically unrelated to heme-copper oxidases, that was found to promote virulence in some bacterial pathogens. Cytochrome bd from Escherichia coli was previously reported to contribute not only to proton motive force generation, but also to bacterial resistance to nitric oxide (NO) and hydrogen peroxide (H2O2). Here, we investigated the interaction of the purified enzyme with peroxynitrite (ONOO(-)), another harmful reactive species produced by the host to kill invading microorganisms. We found that addition of ONOO(-) to cytochrome bd in turnover with ascorbate and N,N,N',N'-tetramethyl-p-phenylenediamine (TMPD) causes the irreversible inhibition of a small (≤15%) protein fraction, due to the NO generated from ONOO(-) and not to ONOO(-) itself. Consistently, addition of ONOO(-) to cells of the E. coli strain GO105/pTK1, expressing cytochrome bd as the only terminal oxidase, caused only a minor (≤5%) irreversible inhibition of O2 consumption, without measurable release of NO. Furthermore, by directly monitoring the kinetics of ONOO(-) decomposition by stopped-flow absorption spectroscopy, it was found that the purified E. coli cytochrome bd in turnover with O2 is able to metabolize ONOO(-) with an apparent turnover rate as high as ~10 mol ONOO(-) (mol enzyme)(-1) s(-1) at 25°C. To the best of our knowledge, this is the first time that the kinetics of ONOO(-) decomposition by a terminal oxidase has been investigated. These results strongly suggest a protective role of cytochrome bd against ONOO(-) damage. Copyright © 2014 Elsevier B.V. All rights reserved.
Schmidt, A.J.; Zacher, A.H.; Gano, S.R.
1996-09-01
The BCD process was applied to dechlorination of two types of PCB-contaminated materials generated from Navy vessel decommissioning activities at Puget Sound Naval Shipyard: insulation of wool felt impregnated with PCB, and PCB-containing paint chips/debris from removal of paint from metal surfaces. The BCD process is a two-stage, low-temperature chemical dehalogenation process. In Stage 1, the materials are mixed with sodium bicarbonate and heated to 350 C. The volatilized halogenated contaminants (eg, PCBs, dioxins, furans), which are collected in a small volume of particulates and granular activated carbon, are decomposed by the liquid-phase reaction (Stage 2) in a stirred-tank reactor, using a high-boiling-point hydrocarbon oil as the reaction medium, with addition of a hydrogen donor, a base (NaOH), and a catalyst. The tests showed that treating wool felt insulation and paint chip wastes with Stage 2 on a large scale is feasible, but compared with current disposal costs for PCB-contaminated materials, using Stage 2 would not be economical at this time. For paint chips generated from shot/sand blasting, the solid-phase BCD process (Stage 1) should be considered, if paint removal activities are accelerated in the future.
ERIC Educational Resources Information Center
Sweeney, William; Lee, James; Abid, Nauman; DeMeo, Stephen
2014-01-01
An experiment is described that determines the activation energy (E[subscript a]) of the iodide-catalyzed decomposition reaction of hydrogen peroxide in a much more efficient manner than previously reported in the literature. Hydrogen peroxide, spontaneously or with a catalyst, decomposes to oxygen and water. Because the decomposition reaction is…
ERIC Educational Resources Information Center
Sweeney, William; Lee, James; Abid, Nauman; DeMeo, Stephen
2014-01-01
An experiment is described that determines the activation energy (E[subscript a]) of the iodide-catalyzed decomposition reaction of hydrogen peroxide in a much more efficient manner than previously reported in the literature. Hydrogen peroxide, spontaneously or with a catalyst, decomposes to oxygen and water. Because the decomposition reaction is…
Liu, Meilin; Li, Baoxin; Zhang, Zhujun; Lin, Jin-Ming
2005-02-01
In the absence of any special luminescence reagent, emission of weak chemiluminescence has been observed during the decomposition of hydrogen peroxide catalyzed by copper(II) in basic aqueous solution. The intensity of the chemiluminescence was greatly enhanced by addition of DNA and was strongly dependent on DNA concentration. Based on these phenomena, a flow-injection chemiluminescence method was established for determination of DNA. The chemiluminescence intensity was linear with DNA concentration in the range 2 x 10(-7)-1 x 10(-5) g L(-1) and the detection limit was 4.1 x 10(-8) g L(-1) (S/N=3). The relative standard deviation was less than 3.0% for 4 x 10(-7) g L(-1) DNA (n=11). The proposed method was satisfactorily applied for determination of DNA in synthetic samples. The possible mechanism of the CL reaction is discussed.
This study examined the mechanism and kinetics of surface catalyzed hydrogen peroxide decomposition and degradation of contaminants in the presence of sand collected from an aquifer and a riverbed. Batch experiments were conducted using variable sand concentrations (0.2 to 1.0&nb...
BASE-CATALYZED DESTRUCTION OF PCBS-NEW DONORS, NEW TRANSFER AGENTS/CATALYSTS
The use of hydrogen transfer agents and catalysts to improve the base-catalyzed decomposition of polychlorinated biphenyls (PCBs) was investigated. The reaction proceeded only in the presence of base, but the rate of PCB disappearance increased with increasing amount of hydrogen ...
BASE-CATALYZED DESTRUCTION OF PCBS-NEW DONORS, NEW TRANSFER AGENTS/CATALYSTS
The use of hydrogen transfer agents and catalysts to improve the base-catalyzed decomposition of polychlorinated biphenyls (PCBs) was investigated. The reaction proceeded only in the presence of base, but the rate of PCB disappearance increased with increasing amount of hydrogen ...
He, Nan; Li, Zhen Hua
2016-04-21
Formic acid decomposition (FAD) reaction has been an innovative way for hydrogen energy. Noble metal catalysts, especially palladium-containing nanoparticles, supported or unsupported, perform well in this reaction. Herein, we considered the simplest model, wherein one Pd atom is used as the FAD catalyst. With high-level theoretical calculations of CCSD(T)/CBS quality, we investigated all possible FAD pathways. The results show that FAD catalyzed by one Pd atom follows a different mechanism compared with that catalyzed by surfaces or larger clusters. At the initial stage of the reaction, FAD follows a dehydration route and is quickly poisoned by CO due to the formation of very stable PdCO. PdCO then becomes the actual catalyst for FAD at temperatures approximately below 1050 K. Beyond 1050 K, there is a switch of catalyst from PdCO to Pd atom. The results also show that dehydration is always favoured over dehydrogenation on either the Pd-atom or PdCO catalyst. On the Pd-atom catalyst, neither dehydrogenation nor dehydration follows the formate mechanism. In contrast, on the PdCO catalyst, dehydrogenation follows the formate mechanism, whereas dehydration does not. We also systematically investigated the performance of 24 density functional theory methods. We found that the performance of the double hybrid mPW2PLYP functional is the best, followed by the B3LYP, B3PW91, N12SX, M11, and B2PLYP functionals.
Anatase-brookite mixed phase nano TiO2 catalyzed homolytic decomposition of ammonium nitrate.
Vargeese, Anuj A; Muralidharan, Krishnamurthi
2011-09-15
Compared to the conventional ammonium perchlorate based solid rocket propellants, burning of ammonium nitrate (AN) based propellants produce environmentally innocuous combustion gases. Application of AN as propellant oxidizer is restricted due to low reactivity and low energetics besides its near room temperature polymorphic phase transition. In the present study, anatase-brookite mixed phase TiO(2) nanoparticles (~ 10 nm) are synthesized and used as catalyst to enhance the reactivity of the environmental friendly propellant oxidizer ammonium nitrate. The activation energy required for the decomposition reactions, computed by differential and non-linear integral isoconversional methods are used to establish the catalytic activity. Presumably, the removal of NH(3) and H(2)O, known inhibitors of ammonium nitrate decomposition reaction, due to the surface reactions on active surface of TiO(2) changes the decomposition pathway and thereby the reactivity.
ERIC Educational Resources Information Center
Nyasulu, Frazier; Barlag, Rebecca
2010-01-01
The reaction kinetics of the iodide-catalyzed decomposition of [subscript 2]O[subscript 2] using the integrated-rate method is described. The method is based on the measurement of the total gas pressure using a datalogger and pressure sensor. This is a modification of a previously reported experiment based on the initial-rate approach. (Contains 2…
ERIC Educational Resources Information Center
Nyasulu, Frazier; Barlag, Rebecca
2010-01-01
The reaction kinetics of the iodide-catalyzed decomposition of [subscript 2]O[subscript 2] using the integrated-rate method is described. The method is based on the measurement of the total gas pressure using a datalogger and pressure sensor. This is a modification of a previously reported experiment based on the initial-rate approach. (Contains 2…
Adaptive Fourier decomposition based ECG denoising.
Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming
2016-10-01
A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition.
1990-02-01
decomposition temperature. Aaded catalyst appears to decrease m/e 70 (1,2,4- oxadiazole ?) formation at low temperature, but to increase it slightly at...Unknown A (1,2,4- oxadiazole ?), from HMX Decomposition......................................................... 17 18 Typical Mass Spectrum of...formation of 1,3,5-triazine and Unknown A (1,2,4- oxadiazole ?) were also studied. II. EXPERIMENTAL The HMX-GAP and HMX-PEG compositions were prepared at
Steganography based on pixel intensity value decomposition
NASA Astrophysics Data System (ADS)
Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.
2014-05-01
This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.
Growth and Detachment of Oxygen Bubbles Induced by Gold-Catalyzed Decomposition of Hydrogen Peroxide
2017-01-01
Whereas bubble growth out of gas-oversatured solutions has been quite well understood, including the formation and stability of surface nanobubbles, this is not the case for bubbles forming on catalytic surfaces due to catalytic reactions, though it has important implications for gas evolution reactions and self-propulsion of micro/nanomotors fueled by bubble release. In this work we have filled this gap by experimentally and theoretically examining the growth and detachment dynamics of oxygen bubbles from hydrogen peroxide decomposition catalyzed by gold. We measured the bubble radius R(t) as a function of time by confocal microscopy and find R(t) ∝ t1/2. This diffusive growth behavior demonstrates that the bubbles grow from an oxygen-oversaturated environment. For several consecutive bubbles detaching from the same position in a short period of time, a well-repeated growing behavior is obtained from which we conclude the absence of noticeable depletion effect of oxygen from previous bubbles or increasing oversaturation from the gas production. In contrast, for two bubbles far apart either in space or in time, substantial discrepancies in their growth rates are observed, which we attribute to the variation in the local gas oversaturation. The current results show that the dynamical evolution of bubbles is influenced by comprehensive effects combining chemical catalysis and physical mass transfer. Finally, we find that the size of the bubbles at the moment of detachment is determined by the balance between buoyancy and surface tension and by the detailed geometry at the bubble’s contact line. PMID:28983387
Lv, Pengyu; Le The, Hai; Eijkel, Jan; Van den Berg, Albert; Zhang, Xuehua; Lohse, Detlef
2017-09-28
Whereas bubble growth out of gas-oversatured solutions has been quite well understood, including the formation and stability of surface nanobubbles, this is not the case for bubbles forming on catalytic surfaces due to catalytic reactions, though it has important implications for gas evolution reactions and self-propulsion of micro/nanomotors fueled by bubble release. In this work we have filled this gap by experimentally and theoretically examining the growth and detachment dynamics of oxygen bubbles from hydrogen peroxide decomposition catalyzed by gold. We measured the bubble radius R(t) as a function of time by confocal microscopy and find R(t) ∝ t(1/2). This diffusive growth behavior demonstrates that the bubbles grow from an oxygen-oversaturated environment. For several consecutive bubbles detaching from the same position in a short period of time, a well-repeated growing behavior is obtained from which we conclude the absence of noticeable depletion effect of oxygen from previous bubbles or increasing oversaturation from the gas production. In contrast, for two bubbles far apart either in space or in time, substantial discrepancies in their growth rates are observed, which we attribute to the variation in the local gas oversaturation. The current results show that the dynamical evolution of bubbles is influenced by comprehensive effects combining chemical catalysis and physical mass transfer. Finally, we find that the size of the bubbles at the moment of detachment is determined by the balance between buoyancy and surface tension and by the detailed geometry at the bubble's contact line.
Distributed Prognostics based on Structural Model Decomposition
NASA Technical Reports Server (NTRS)
Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, I.
2014-01-01
Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATIONS
Zou, Min Wang, Xin Jiang, Xiaohong Lu, Lude
2014-05-01
Catalyzed thermal decomposition process of ammonium perchlorate (AP) over neodymium oxide (Nd{sub 2}O{sub 3}) was investigated. Catalytic performances of nanometer-sized Nd{sub 2}O{sub 3} and micrometer-sized Nd{sub 2}O{sub 3} were evaluated by differential scanning calorimetry (DSC). In contrast to universal concepts, catalysts in different sizes have nearly similar catalytic activities. Based on structural and morphological variation of the catalysts during the reaction, combined with mass spectrum analyses and studies of unmixed style, a new understanding of this catalytic process was proposed. We believed that the newly formed chloride neodymium oxide (NdOCl) was the real catalytic species in the overall thermal decomposition of AP over Nd{sub 2}O{sub 3}. Meanwhile, it was the “self-distributed” procedure which occurred within the reaction that also worked for the improvement of overall catalytic activities. This work is of great value in understanding the roles of micrometer-sized catalysts used in heterogeneous reactions, especially the solid–solid reactions which could generate a large quantity of gaseous species. - Graphical abstract: In-situ and self-distributed reaction process in thermal decomposition of AP catalyzed by Nd{sub 2}O{sub 3}. - Highlights: • Micro- and nano-Nd{sub 2}O{sub 3} for catalytic thermal decomposition of AP. • No essential differences on their catalytic performances. • Structural and morphological variation of catalysts digs out catalytic mechanism. • This catalytic process is “in-situ and self-distributed” one.
Model-based multiple patterning layout decomposition
NASA Astrophysics Data System (ADS)
Guo, Daifeng; Tian, Haitong; Du, Yuelin; Wong, Martin D. F.
2015-10-01
As one of the most promising next generation lithography technologies, multiple patterning lithography (MPL) plays an important role in the attempts to keep in pace with 10 nm technology node and beyond. With feature size keeps shrinking, it has become impossible to print dense layouts within one single exposure. As a result, MPL such as double patterning lithography (DPL) and triple patterning lithography (TPL) has been widely adopted. There is a large volume of literature on DPL/TPL layout decomposition, and the current approach is to formulate the problem as a classical graph-coloring problem: Layout features (polygons) are represented by vertices in a graph G and there is an edge between two vertices if and only if the distance between the two corresponding features are less than a minimum distance threshold value dmin. The problem is to color the vertices of G using k colors (k = 2 for DPL, k = 3 for TPL) such that no two vertices connected by an edge are given the same color. This is a rule-based approach, which impose a geometric distance as a minimum constraint to simply decompose polygons within the distance into different masks. It is not desired in practice because this criteria cannot completely capture the behavior of the optics. For example, it lacks of sufficient information such as the optical source characteristics and the effects between the polygons outside the minimum distance. To remedy the deficiency, a model-based layout decomposition approach to make the decomposition criteria base on simulation results was first introduced at SPIE 2013.1 However, the algorithm1 is based on simplified assumption on the optical simulation model and therefore its usage on real layouts is limited. Recently AMSL2 also proposed a model-based approach to layout decomposition by iteratively simulating the layout, which requires excessive computational resource and may lead to sub-optimal solutions. The approach2 also potentially generates too many stiches. In this
Lee, Hongshin; Lee, Hye-Jin; Sedlak, David L; Lee, Changha
2013-07-01
The decomposition of hydrogen peroxide catalyzed by iron and copper leads to the generation of reactive oxidants capable of oxidizing various organic compounds. However, the specific nature of the reactive oxidants is still unclear, with evidence suggesting the production of hydroxyl radical or high-valent metal species. To identify the reactive species in the Fenton system, the oxidation of a series of different compounds (phenol, benzoic acid, methanol, Reactive Black 5 and arsenite) was studied for iron- and copper-catalyzed reactions at varying pH values. At lower pH values, more reactive oxidants appear to be formed in both iron and copper-catalyzed systems. The aromatic compounds, phenol and benzoic acid, were not oxidized under neutral or alkaline pH conditions, whereas methanol, Reactive Black 5, and arsenite were oxidized to a different degree, depending on the catalytic system. The oxidants responsible for the oxidation of compounds at neutral and alkaline pH values are likely to be high-valent metal complexes of iron and copper (i.e., ferryl and cupryl ions).
Rank-based decompositions of morphological templates.
Sussner, P; Ritter, G X
2000-01-01
Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.
Hyder, M.L.
1997-03-17
The effect of oxygen on the copper-catalyzed hydrolysis of phenyl borates containing from one to four phenyl groups was studied in 1 M aqueous sodium hydroxide solution at 59 degrees C. The results are tentatively explained if the effective catalyst for each of the reactions is either cupric or cuprous ion, with the latter being present in significant concentration only in the absence of air.
Mavri, Janez; Matute, Ricardo A; Chu, Zhen T; Vianello, Robert
2016-04-14
Brain monoamines regulate many centrally mediated body functions, and can cause adverse symptoms when they are out of balance. A starting point to address challenges raised by the increasing burden of brain diseases is to understand, at atomistic level, the catalytic mechanism of an essential amine metabolic enzyme-monoamine oxidase B (MAO B). Recently, we demonstrated that the rate-limiting step of MAO B catalyzed conversion of amines into imines represents the hydride anion transfer from the substrate α-CH2 group to the N5 atom of the flavin cofactor moiety. In this article we simulated for MAO B catalyzed dopamine decomposition the effects of nuclear tunneling by the calculation of the H/D kinetic isotope effect. We applied path integral quantization of the nuclear motion for the methylene group and the N5 atom of the flavin moiety in conjunction with the QM/MM treatment on the empirical valence bond (EVB) level for the rest of the enzyme. The calculated H/D kinetic isotope effect of 12.8 ± 0.3 is in a reasonable agreement with the available experimental data for closely related biogenic amines, which gives strong support for the proposed hydride mechanism. The results are discussed in the context of tunneling in enzyme centers and advent of deuterated drugs into clinical practice.
A PERFORMANCE HISTORY OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS
Remediation of halogenated organic compounds--such as polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs)--poses a challenge because these compounds are resistant to microbial attack and to degradation by many com...
A PERFORMANCE HISTORY OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS
Remediation of halogenated organic compounds--such as polychlorinated biphenyls (PCBs), polychlorinated dibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans (PCDFs)--poses a challenge because these compounds are resistant to microbial attack and to degradation by many com...
Zhang, Yuanyuan; Lin, Yi-Pin
2013-10-01
The stability of Pb(IV) corrosion product PbO2 has been linked to lead contamination in chloraminated drinking water. Recent studies have shown that autodecomposition of monochloramine (NH2Cl) can cause lead release from PbO2 via reductive dissolution. Bromide (Br(-)) is a known catalyst for NH2Cl decomposition. In this study, we investigated whether Br(-)-catalyzed NH2Cl decomposition could further enhance lead release from PbO2. Our results showed that Br(-_)catalyzed NH2Cl decomposition did accelerate the reduction of PbO2, and the rate was enhanced by the lower pH value, higher Br(-), and NH2Cl concentrations. A single linear correlation was found between the amount of NH2Cl decomposed and the amount of total Pb(II) released either in the absence or presence of Br(-), suggesting that Br(-)-catalyzed NH2Cl decomposition and NH2Cl autodecomposition may generate the same intermediate toward PbO2 reduction. The kinetics of total Pb(II) release can be successfully modeled by considering the overall rate of NH2Cl decomposition with NOH as the reactive intermediate responsible for PbO2 reduction. Our findings suggested that special attentions on lead contamination should be paid to systems with PbO2 scales and high Br(-)-containing source waters when switching disinfectant from free chlorine to monochloramine.
Overlapping Community Detection based on Network Decomposition
NASA Astrophysics Data System (ADS)
Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin
2016-04-01
Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.
Overlapping Community Detection based on Network Decomposition
Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin
2016-01-01
Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904
Gate-based decomposition of index generation functions
NASA Astrophysics Data System (ADS)
Łuba, Tadeusz; Borowik, Grzegorz; Jankowski, Cezary
2016-09-01
Index Generation Functions may be useful in distribution of IP addresses, virus scanning, or undesired data detection. Traditional approach leads to universal cells based decomposition. In this paper an original method is proposed. The proposed multilevel logic synthesis method based on functional decomposition uses gates instead of cells. Furthermore, it preserves advantages of functional decomposition and is well suited for ROM-based synthesis of Index Generation Functions.
Neurocomputing strategies in decomposition based structural design
NASA Technical Reports Server (NTRS)
Szewczyk, Z.; Hajela, P.
1993-01-01
The present paper explores the applicability of neurocomputing strategies in decomposition based structural optimization problems. It is shown that the modeling capability of a backpropagation neural network can be used to detect weak couplings in a system, and to effectively decompose it into smaller, more tractable, subsystems. When such partitioning of a design space is possible, parallel optimization can be performed in each subsystem, with a penalty term added to its objective function to account for constraint violations in all other subsystems. Dependencies among subsystems are represented in terms of global design variables, and a neural network is used to map the relations between these variables and all subsystem constraints. A vector quantization technique, referred to as a z-Network, can effectively be used for this purpose. The approach is illustrated with applications to minimum weight sizing of truss structures with multiple design constraints.
Base-Catalyzed Depolymerization of Biorefinery Lignins
Katahira, Rui; Mittal, Ashutosh; McKinney, Kellene; ...
2016-01-12
Lignocellulosic biorefineries will produce a substantial pool of lignin-enriched residues, which are currently slated to be burned for heat and power. Going forward, however, valorization strategies for residual solid lignin will be essential to the economic viability of modern biorefineries. To achieve these strategies, effective lignin depolymerization processes will be required that can convert specific lignin-enriched biorefinery substrates into products of sufficient value and market size. Base-catalyzed depolymerization (BCD) of lignin using sodium hydroxide and other basic media has been shown to be an effective depolymerization approach when using technical and isolated lignins relevant to the pulp and paper industry.more » Moreover, to gain insights in the application of BCD to lignin-rich, biofuels-relevant residues, here we apply BCD with sodium hydroxide at two catalyst loadings and temperatures of 270, 300, and 330 °C for 40 min to residual biomass from typical and emerging biochemical conversion processes. We obtained mass balances for each fraction from BCD, and characterized the resulting aqueous and solid residues using gel permeation chromatography, NMR, and GC–MS. When taken together, these results indicate that a significant fraction (45–78%) of the starting lignin-rich material can be depolymerized to low molecular weight, water-soluble species. The yield of the aqueous soluble fraction depends significantly on biomass processing method used prior to BCD. Namely, dilute acid pretreatment results in lower water-soluble yields compared to biomass processing that involves no acid pretreatment. We also find that the BCD product selectivity can be tuned with temperature to give higher yields of methoxyphenols at lower temperature, and a higher relative content of benzenediols with a greater extent of alkylation on the aromatic rings at higher temperature. Our study shows that residual, lignin-rich biomass produced from conventional and
Middleton, Beth A.
2014-01-01
A cornerstone of ecosystem ecology, decomposition was recognized as a fundamental process driving the exchange of energy in ecosystems by early ecologists such as Lindeman 1942 and Odum 1960). In the history of ecology, studies of decomposition were incorporated into the International Biological Program in the 1960s to compare the nature of organic matter breakdown in various ecosystem types. Such studies still have an important role in ecological studies of today. More recent refinements have brought debates on the relative role microbes, invertebrates and environment in the breakdown and release of carbon into the atmosphere, as well as how nutrient cycling, production and other ecosystem processes regulated by decomposition may shift with climate change. Therefore, this bibliography examines the primary literature related to organic matter breakdown, but it also explores topics in which decomposition plays a key supporting role including vegetation composition, latitudinal gradients, altered ecosystems, anthropogenic impacts, carbon storage, and climate change models. Knowledge of these topics is relevant to both the study of ecosystem ecology as well projections of future conditions for human societies.
Small-Scale Kinetic Study of the Catalyzed Decomposition of Hydrogen Peroxide
NASA Astrophysics Data System (ADS)
Ragsdale, Ronald O.; Vanderhooft, Jan C.; Zipp, Arden P.
1998-02-01
The rate of decomposition of hydrogen peroxide with pyrolusite as a catalyst was studied directly by following the formation of oxygen bubbles. The apparatus consisted of a barrel from a 2-ml Beral pipet inserted over a micropipet tip which was fitted into a one-hole stopper. The stopper assembly was placed in a 20-mL glass bottle reaction vessel. The hydrogen peroxide can be obtained from the super market and the catalyst, a piece of pyrolusite, can be recycled. The reaction order was found to be 1.1 + 0.2 by 240 pairs of students. The activation energy was 35 + 14 kJ. Reproducible data have also been obtained with the minerals, psilomelane, maganite, and groutite as catalysts.
Tao, Zhimin; Raffel, Ryan A; Souid, Abdul-Kader; Goodisman, Jerry
2009-04-08
The kinetics of the glucose oxidase-catalyzed reaction of glucose with O2, which produces gluconic acid and hydrogen peroxide, and the catalase-assisted breakdown of hydrogen peroxide to generate oxygen, have been measured via the rate of O2 depletion or production. The O2 concentrations in air-saturated phosphate-buffered salt solutions were monitored by measuring the decay of phosphorescence from a Pd phosphor in solution; the decay rate was obtained by fitting the tail of the phosphorescence intensity profile to an exponential. For glucose oxidation in the presence of glucose oxidase, the rate constant determined for the rate-limiting step was k = (3.0 +/- 0.7) x 10(4) M(-1) s(-1) at 37 degrees C. For catalase-catalyzed H2O2 breakdown, the reaction order in [H2O2] was somewhat greater than unity at 37 degrees C and well above unity at 25 degrees C, suggesting different temperature dependences of the rate constants for various steps in the reaction. The two reactions were combined in a single experiment: addition of glucose oxidase to glucose-rich cell-free media caused a rapid drop in [O2], and subsequent addition of catalase caused [O2] to rise and then decrease to zero. The best fit of [O2] to a kinetic model is obtained with the rate constants for glucose oxidation and peroxide decomposition equal to 0.116 s(-1) and 0.090 s(-1) respectively. Cellular respiration in the presence of glucose was found to be three times as rapid as that in glucose-deprived cells. Added NaCN inhibited O2 consumption completely, confirming that oxidation occurred in the cellular mitochondrial respiratory chain.
Cobalt-based Catalysts for Ammonia Decomposition
Lendzion-Bielun, Zofia; Narkiewicz, Urszula; Arabczyk, Walerian
2013-01-01
An effect of promoters such as calcium, aluminium, and potassium oxides and also addition of chromium and manganese on the structure of cobalt catalysts was examined. Studies of the catalytic ammonia decomposition over the cobalt catalysts are presented. The studies of the ammonia decomposition were carried out for various ammonia-hydrogen mixtures in which ammonia concentration varied in the range from 10% to 100%. Co(0) catalyst, promoted by oxides of aluminium, calcium, and potassium, showed the highest activity in the ammonia decomposition reaction. Contrary to expectations, it was found that chromium and manganese addition into the catalysts decreased their activity. PMID:28809280
Evolution-Based Functional Decomposition of Proteins
Rivoire, Olivier; Reynolds, Kimberly A.; Ranganathan, Rama
2016-01-01
The essential biological properties of proteins—folding, biochemical activities, and the capacity to adapt—arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment—a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation. PMID:27254668
Evolution-Based Functional Decomposition of Proteins.
Rivoire, Olivier; Reynolds, Kimberly A; Ranganathan, Rama
2016-06-01
The essential biological properties of proteins-folding, biochemical activities, and the capacity to adapt-arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment-a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation.
Revision of singlet quantum yields in the catalyzed decomposition of cyclic peroxides.
Almeida de Oliveira, Marcelo; Bartoloni, Fernando Heering; Augusto, Felipe Alberto; Ciscato, Luiz Francisco Monteiro Leite; Bastos, Erick Leite; Baader, Wilhelm Josef
2012-12-07
The chemiluminescence of cyclic peroxides activated by oxidizable fluorescent dyes is an example of chemically initiated electron exchange luminescence (CIEEL), which has been used also to explain the efficient bioluminescence of fireflies. Diphenoyl peroxide and dimethyl-1,2-dioxetanone were used as model compounds for the development of this CIEEL mechanism. However, the chemiexcitation efficiency of diphenoyl peroxide was found to be much lower than originally described. In this work, we redetermine the chemiexcitation quantum efficiency of dimethyl-1,2-dioxetanone, a more adequate model for firefly bioluminescence, and found a singlet quantum yield (Φ(S)) of 0.1%, a value at least 2 orders of magnitude lower than previously reported. Furthermore, we synthesized two other 1,2-dioxetanone derivatives and confirm the low chemiexcitation efficiency (Φ(S) < 0.1%) of the intermolecular CIEEL-activated decomposition of this class of cyclic peroxides. These results are compared with other chemiluminescent reactions, supporting the general trend that intermolecular CIEEL systems are much less efficient in generating singlet excited states than analogous intramolecular processes (Φ(S) ≈ 50%), with the notable exception of the peroxyoxalate reaction (Φ(S) ≈ 60%).
The constraint based decomposition (CBD) training architecture.
Draghici, S
2001-05-01
The Constraint Based Decomposition (CBD) is a constructive neural network technique that builds a three or four layer network, has guaranteed convergence and can deal with binary, n-ary, class labeled and real-value problems. CBD is shown to be able to solve complicated problems in a simple, fast and reliable manner. The technique is further enhanced by two modifications (locking detection and redundancy elimination) which address the training speed and the efficiency of the internal representation built by the network. The redundancy elimination aims at building more compact architectures while the locking detection aims at improving the training speed. The computational cost of the redundancy elimination is negligible and this enhancement can be used for any problem. However, the computational cost of the locking detection is exponential in the number of dimensions and should only be used in low dimensional spaces. The experimental results show the performance of the algorithm presented in a series of classical benchmark problems including the 2-spiral problem and the Iris, Wine, Glass, Lenses, Ionosphere, Lung cancer, Pima Indians, Bupa, TicTacToe, Balance and Zoo data sets from the UCI machine learning repository. CBD's generalization accuracy is compared with that of C4.5, C4.5 with rules, incremental decision trees, oblique classifiers, linear machine decision trees, CN2, learning vector quantization (LVQ), backpropagation, nearest neighbor, Q* and radial basis functions (RBFs). CBD provides the second best average accuracy on the problems tested as well as the best reliability (the lowest standard deviation).
Development of a Lewis Base Catalyzed Selenocyclization Reaction
ERIC Educational Resources Information Center
Collins, William
2009-01-01
The concept of Lewis base activation of selenium Lewis acids has been effectively reduced to practice in the Lewis base catalyzed selenofunctionalization of unactivated olefins. In this reaction, the weakly acidic species, "N"-phenylselenyl succinimide, is cooperatively activated by the addition of a "soft" Lewis base donor (phosphine sulfides,…
Development of a Lewis Base Catalyzed Selenocyclization Reaction
ERIC Educational Resources Information Center
Collins, William
2009-01-01
The concept of Lewis base activation of selenium Lewis acids has been effectively reduced to practice in the Lewis base catalyzed selenofunctionalization of unactivated olefins. In this reaction, the weakly acidic species, "N"-phenylselenyl succinimide, is cooperatively activated by the addition of a "soft" Lewis base donor (phosphine sulfides,…
ERIC Educational Resources Information Center
Barlag, Rebecca; Nyasulu, Frazier
2010-01-01
A wash bottle water displacement scheme is used to determine the kinetics of the iodide-catalyzed H[subscript 2]O[subscript 2] decomposition reaction. The reagents (total volume 5.00 mL) are added to a test tube that is placed in a wash bottle containing water. The mass of the water displaced in [approximately]60 s is measured. The reaction is…
ERIC Educational Resources Information Center
Barlag, Rebecca; Nyasulu, Frazier
2010-01-01
A wash bottle water displacement scheme is used to determine the kinetics of the iodide-catalyzed H[subscript 2]O[subscript 2] decomposition reaction. The reagents (total volume 5.00 mL) are added to a test tube that is placed in a wash bottle containing water. The mass of the water displaced in [approximately]60 s is measured. The reaction is…
NASA Astrophysics Data System (ADS)
Li, Duan; Xu, Lijun; Li, Xiaolu
2017-04-01
To measure the distances and properties of the objects within a laser footprint, a decomposition method for full-waveform light detection and ranging (LiDAR) echoes is proposed. In this method, firstly, wavelet decomposition is used to filter the noise and estimate the noise level in a full-waveform echo. Secondly, peak and inflection points of the filtered full-waveform echo are used to detect the echo components in the filtered full-waveform echo. Lastly, particle swarm optimization (PSO) is used to remove the noise-caused echo components and optimize the parameters of the most probable echo components. Simulation results show that the wavelet-decomposition-based filter is of the best improvement of SNR and decomposition success rates than Wiener and Gaussian smoothing filters. In addition, the noise level estimated using wavelet-decomposition-based filter is more accurate than those estimated using other two commonly used methods. Experiments were carried out to evaluate the proposed method that was compared with our previous method (called GS-LM for short). In experiments, a lab-build full-waveform LiDAR system was utilized to provide eight types of full-waveform echoes scattered from three objects at different distances. Experimental results show that the proposed method has higher success rates for decomposition of full-waveform echoes and more accurate parameters estimation for echo components than those of GS-LM. The proposed method based on wavelet decomposition and PSO is valid to decompose the more complicated full-waveform echoes for estimating the multi-level distances of the objects and measuring the properties of the objects in a laser footprint.
Contrast Enhancement Based on Intrinsic Image Decomposition.
Yue, Huanjing; Yang, Jingyu; Sun, Xiaoyan; Wu, Feng; Hou, Chunping
2017-05-10
In this paper, we propose to introduce intrinsic image decomposition priors into decomposition models for contrast enhancement. Since image decomposition is a highly ill-posed problem, we introduce constraints on both reflectance and illumination layers to yield a highly reliable solution. We regularize the reflectance layer to be piecewise constant by introducing a weighted `1 norm constraint on neighboring pixels according to the color similarity, so that the decomposed reflectance would not be affected much by the illumination information. The illumination layer is regularized by a piecewise smoothness constraint. The proposed model is effectively solved by the Split Bregman algorithm. Then, by adjusting the illumination layer, we obtain the enhancement result. To avoid potential color artifacts introduced by illumination adjusting and reduce computing complexity, the proposed decomposition model is performed on the value channel in HSV space. Experiment results demonstrate that the proposed method performs well for a wide variety of images, and achieves better or comparable subjective and objective quality compared with state-of-the-art methods.
Schowen, K B; Smissman, E E; Stephen, W F
1975-03-01
The base- and cholinestrase-catalyzed hydrolyses of the following optically active analogs of acetylcholine were studied: 3 (a)-trimethylammonium-2(a)-acetoxy-trans-decalin iodide, threo- and erythro-alpha, beta-dimethylacetylcholine iodide, alpha-methylacetylcholine, and beta-methylacetylcholine. Evidence that the optimum dihedral +N-C-C-O angle in the transition state for acetylcholinesterase hydrolysis of acetylcholine analogs is positive and anticlinal is given. The data obtained suggest that acetylcholine undergoes a geometrically flexible mode of attachment to the enzyme.
Kinetic energy decomposition scheme based on information theory.
Imamura, Yutaka; Suzuki, Jun; Nakai, Hiromi
2013-12-15
We proposed a novel kinetic energy decomposition analysis based on information theory. Since the Hirshfeld partitioning for electron densities can be formulated in terms of Kullback-Leibler information deficiency in information theory, a similar partitioning for kinetic energy densities was newly proposed. The numerical assessments confirm that the current kinetic energy decomposition scheme provides reasonable chemical pictures for ionic and covalent molecules, and can also estimate atomic energies using a correction with viral ratios. Copyright © 2013 Wiley Periodicals, Inc.
Embedding color watermarks in color images based on Schur decomposition
NASA Astrophysics Data System (ADS)
Su, Qingtang; Niu, Yugang; Liu, Xianxi; Zhu, Yu
2012-04-01
In this paper, a blind dual color image watermarking scheme based on Schur decomposition is introduced. This is the first time to use Schur decomposition to embed color image watermark in color host image, which is different from using the binary image as watermark. By analyzing the 4 × 4 unitary matrix U via Schur decomposition, we can find that there is a strong correlation between the second row first column element and the third row first column element. This property can be explored for embedding watermark and extracting watermark in the blind manner. Since Schur decomposition is an intermediate step in SVD decomposition, the proposed method requires less number of computations. Experimental results show that the proposed scheme is robust against most common attacks including JPEG lossy compression, JPEG 2000 compression, low-pass filtering, cropping, noise addition, blurring, rotation, scaling and sharpening et al. Moreover, the proposed algorithm outperforms the closely related SVD-based algorithm and the spatial-domain algorithm.
Feature based volume decomposition for automatic hexahedral mesh generation
LU,YONG; GADH,RAJIT; TAUTGES,TIMOTHY J.
2000-02-21
Much progress has been made through these years to achieve automatic hexahedral mesh generation. While general meshing algorithms that can take on general geometry are not there yet; many well-proven automatic meshing algorithms now work on certain classes of geometry. This paper presents a feature based volume decomposition approach for automatic Hexahedral Mesh generation. In this approach, feature recognition techniques are introduced to determine decomposition features from a CAD model. The features are then decomposed and mapped with appropriate automatic meshing algorithms suitable for the correspondent geometry. Thus a formerly unmeshable CAD model may become meshable. The procedure of feature decomposition is recursive: sub-models are further decomposed until either they are matched with appropriate meshing algorithms or no more decomposition features are detected. The feature recognition methods employed are convexity based and use topology and geometry information, which is generally available in BREP solid models. The operations of volume decomposition are also detailed in the paper. The final section, the capability of the feature decomposer is demonstrated over some complicated manufactured parts.
A decomposition method based on a model of continuous change.
Horiuchi, Shiro; Wilmoth, John R; Pletcher, Scott D
2008-11-01
A demographic measure is often expressed as a deterministic or stochastic function of multiple variables (covariates), and a general problem (the decomposition problem) is to assess contributions of individual covariates to a difference in the demographic measure (dependent variable) between two populations. We propose a method of decomposition analysis based on an assumption that covariates change continuously along an actual or hypothetical dimension. This assumption leads to a general model that logically justifies the additivity of covariate effects and the elimination of interaction terms, even if the dependent variable itself is a nonadditive function. A comparison with earlier methods illustrates other practical advantages of the method: in addition to an absence of residuals or interaction terms, the method can easily handle a large number of covariates and does not require a logically meaningful ordering of covariates. Two empirical examples show that the method can be applied flexibly to a wide variety of decomposition problems. This study also suggests that when data are available at multiple time points over a long interval, it is more accurate to compute an aggregated decomposition based on multiple subintervals than to compute a single decomposition for the entire study period.
Neural network based decomposition in optimal structural synthesis
NASA Technical Reports Server (NTRS)
Hajela, P.; Berke, L.
1992-01-01
The present paper describes potential applications of neural networks in the multilevel decomposition based optimal design of structural systems. The generic structural optimization problem of interest, if handled as a single problem, results in a large dimensionality problem. Decomposition strategies allow for this problem to be represented by a set of smaller, decoupled problems, for which solutions may either be obtained with greater ease or may be obtained in parallel. Neural network models derived through supervised training, are used in two distinct modes in this work. The first uses neural networks to make available efficient analysis models for use in repetitive function evaluations as required by the optimization algorithm. In the second mode, neural networks are used to represent the coupling that exists between the decomposed subproblems. The approach is illustrated by application to the multilevel decomposition-based synthesis of representative truss and frame structures.
Kovtyukhova, N.I.; Belousov, V.M.; Konishevskaya, G.A.; Novikov, Yu.N.; Vol'pin, M.E.
1987-05-01
The kinetics of the decomposition of cyclohexenyl hydroperoxide (CHHP) has been studied on a graphite intercalation compound with MoCl/sub 5/ in cyclohexene solution in the temperature range 50-75/sup 0/C. A reaction scheme has been proposed, including the participation of the catalyst in the radical decomposition of CHHP and epoxidation by it of cyclohexene. Based on the proposed scheme, kinetic equations have been obtained, which effectively represent the experimental data.
Base-Catalyzed Depolymerization of Lignin: Separation of Monomers
Vigneault, A.; Johnson, D. K.; Chornet, E.
2007-12-01
In our quest for fractionating lignocellulosic biomass and valorizing specific constitutive fractions, we have developed a strategy for the separation of 12 added value monomers generated during the hydrolytic based-catalyzed depolymerization of a Steam Exploded Aspen Lignin. The separation strategy combines liquid-liquid-extraction (LLE), followed by vacuum distillation, liquid chromatography (LC) and crystallization. LLE, vacuum distillation and flash LC were tested experimentally. Batch vacuum distillation produced up to 4 fractions. Process simulation confirmed that a series of 4 vacuum distillation columns could produce 5 distinct monomer streams, 3 of which require further chromatography and crystallization for purification.
Beyer, H; Meini, S; Tsiouvaras, N; Piana, M; Gasteiger, H A
2013-07-14
The decomposition of lithium peroxide during the charging process of lithium-air batteries is investigated. A novel preparation method for electrodes in the discharged state, i.e., prefilled with Li2O2 using polyethylene oxide as a binder, is presented. The composition and reactivity of Li2O2-prefilled electrodes are examined by thermal analysis coupled with on-line mass spectrometry. Voltage profiles and gas evolution during the charging process of Li2O2-prefilled electrodes in battery cells are correlated with the thermal decomposition process of Li2O2 and its impact on other electrode compounds. It is found that both thermal Li2O2 decomposition and the electrochemical decomposition of Li2O2 during charging enhance the oxidation of the electrolyte, the binder, and/or carbon, which is suggested to be due to the formation of "nascent" oxygen during Li2O2 decomposition into O2 and Li2O (thermally) or into O2 and lithium ions (electrochemically).
Decomposition of Perfluorocompounds on Alumina-Based Catalyst
Kanno, Shuichi; Tamata, Shin; Kurokawa, Hideaki
2004-03-31
The control of the atmospheric release of PFCs (perfluorocompounds) is an important environmental problem worldwide. PFCs are powerful greenhouse gases used by the semiconductor and liquid crystal industries as etching and cleaning agents. We developed a catalyst that decomposes PFCs with only water. Al2O3 was selected from the survey of some single metal-oxide catalysts. Addition of another metal-oxide improved the decomposition ratio and durability. The Al2O3-based catalyst decomposed CF4, C2F6, C3F8, C4F8, NF3 and SF6 by more than 99% at 750 degrees Celsius. Furthermore, our catalyst retained a high decomposition ratio as demonstrated by a continuous run for about 4000 hours at 700-750 degrees Celsius. The influence of chlorine as an impurity with regard to the SF6 decomposition ratio on the catalyst was examined. SF6 was decomposed at more than 99% during 8 hours in the presence of 400 ppm chlorine. Chlorine concentration in the outlet gas was less than TLV. No chlorine compounds were found by X-ray diffraction analysis of the used catalyst. That is, the hydrogenation of chlorine did not inhibit the surface catalytic reaction for PFC. Also, CF4 was decomposed at the condition of 1.4% of high concentration. The conversion remained higher than 99% throughout during a durability test. Furthermore, we investigated a large-scale decomposition system in the paper.
Gesture Based Control and EMG Decomposition
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Chang, Mindy H.; Knuth, Kevin H.
2005-01-01
This paper presents two probabilistic developments for use with Electromyograms (EMG). First described is a new-electric interface for virtual device control based on gesture recognition. The second development is a Bayesian method for decomposing EMG into individual motor unit action potentials. This more complex technique will then allow for higher resolution in separating muscle groups for gesture recognition. All examples presented rely upon sampling EMG data from a subject's forearm. The gesture based recognition uses pattern recognition software that has been trained to identify gestures from among a given set of gestures. The pattern recognition software consists of hidden Markov models which are used to recognize the gestures as they are being performed in real-time from moving averages of EMG. Two experiments were conducted to examine the feasibility of this interface technology. The first replicated a virtual joystick interface, and the second replicated a keyboard. Moving averages of EMG do not provide easy distinction between fine muscle groups. To better distinguish between different fine motor skill muscle groups we present a Bayesian algorithm to separate surface EMG into representative motor unit action potentials. The algorithm is based upon differential Variable Component Analysis (dVCA) [l], [2] which was originally developed for Electroencephalograms. The algorithm uses a simple forward model representing a mixture of motor unit action potentials as seen across multiple channels. The parameters of this model are iteratively optimized for each component. Results are presented on both synthetic and experimental EMG data. The synthetic case has additive white noise and is compared with known components. The experimental EMG data was obtained using a custom linear electrode array designed for this study.
Contourlet based image watermarking using QR decomposition
NASA Astrophysics Data System (ADS)
Mitra, Priyanka; Gunjan, Reena; Gaur, M. S.
2013-01-01
The paper presents an image watermarking algorithm based on Contourlet Transform (CT) and QR factorization method. Contourlet Transform is used to transform both the cover and watermark image into subbands. The watermarking is applied to the Contourlet Transform as the human visual system is comparatively less sensitive to edges of the image. The low frequency coefficients of an image contain the highest energy. Thus the lowest frequency coefficients of the contourlet transformed original and watermark image are selected for watermarking. The selected coefficients are then decomposed using QR factorization method. The QR factorized coefficients of watermark image is embedded into the QR factorized original image values. Inverse QR and inverse CT is then applied on the watermark embedded coefficients of image to obtain the watermarked image. Experimental results show that the proposed algorithm is a better technique as compared to other watermarking schemes based on Contourlet Transform. The proposed watermarking scheme is imperceptible and robust against image processing attacks such as Gaussian noise, scaling, compression, salt and pepper noise.
Electrocardiograph signal denoising based on sparse decomposition.
Zhu, Junjiang; Li, Xiaolu
2017-08-01
Noise in ECG signals will affect the result of post-processing if left untreated. Since ECG is highly subjective, the linear denoising method with a specific threshold working well on one subject could fail on another. Therefore, in this Letter, sparse-based method, which represents every segment of signal using different linear combinations of atoms from a dictionary, is used to denoise ECG signals, with a view to myoelectric interference existing in ECG signals. Firstly, a denoising model for ECG signals is constructed. Then the model is solved by matching pursuit algorithm. In order to get better results, four kinds of dictionaries are investigated with the ECG signals from MIT-BIH arrhythmia database, compared with wavelet transform (WT)-based method. Signal-noise ratio (SNR) and mean square error (MSE) between estimated signal and original signal are used as indicators to evaluate the performance. The results show that by using the present method, the SNR is higher while the MSE between estimated signal and original signal is smaller.
Beishline, R.R.; Gould, B.; Walker, E.B.; Stuart, D.K.; Schultzski, J.; Shigley, J.K.; Calvert, K.; Dalling, D.K.; Anderson, L.L.
1982-04-23
The zinc chloride catalyzed decomposition of 1,2-dihydronaphthalene (1) at 165 /sup 0/C produces dimers of 1, tetralin, and naphthalene. Zinc chloride functions as a Friedel-Crafts type catalyst by coordinating with a hydroxyl from a water molecule and releasing a proton which initiates a carbonium ion reaction. The stoichiometric role of water has been established by measuring the activity of the zinc chloride-water complex as a function of the degree of hydration of the zinc chloride. The activity maximum occurs at a zinc chloride/water mole ratio of 1:1. Deuterium tracer experiments corroborate the role of water and also verify that the reaction occurs by a carbonium ion mechanism. The carbonium ion nature of the reaction is also inferred by the structures of the products. The 300-MHz/sup 1/H NMR spectra of the dimer products are consistent with the previously reported structures of the compounds.
The General Base in the Thymidylate Synthase Catalyzed Proton Abstraction
Ghosh, Ananda K.; Islam, Zahidul; Krueger, Jonathan; Abeysinghe, Don Thelma; Kohen, Amnon
2015-01-01
The enzyme thymidylate synthase (TSase), an important chemotherapeutic drug target, catalyzes the formation of 2′-deoxythymidine-5′-monophosphate (dTMP), a precursor of one of the DNA building blocks. TSase catalyzes a multi-step mechanism that includes the abstraction of a proton from the C5 of the substrate 2′-deoxyuridine-5′-monophosphate (dUMP). Previous studies on ecTSase proposed that an active-site residue, Y94 serves the role of the general base abstracting this proton. However, since Y94 is neither very basic, nor connected to basic residues, nor located close enough to the pyrimidine proton to be abstracted, the actual identity of this base remains enigmatic. Based on crystal structures, an alternative hypothesis is that the nearest potential proton-acceptor of C5 of dUMP is a water molecule that is part of a hydrogen bond (H-bond) network comprised of several water molecules and several protein residues including H147, E58, N177, and Y94. Here, we examine the role of the residue Y94 in the proton abstraction step by removing its hydroxyl group (Y94F mutant). We investigated the effect of the mutation on the temperature dependence of intrinsic kinetic isotope effects (KIEs) and found that these KIEs are more temperature dependent than those of the wild-type enzyme (WT). These results suggest that the phenolic –OH of Y94 is a component of the transition state for the proton abstraction step. The findings further support the hypothesis that no single functional group is the general base, but a network of bases and hydroxyls (from water molecules and tyrosine) sharing H-bonds across the active site can serve the role of the general base to remove the pyrimidine proton. PMID:25912171
Ab initio modeling of decomposition in iron based alloys
NASA Astrophysics Data System (ADS)
Gorbatov, O. I.; Gornostyrev, Yu. N.; Korzhavyi, P. A.; Ruban, A. V.
2016-12-01
This paper reviews recent progress in the field of ab initio based simulations of structure and properties of Fe-based alloys. We focus on thermodynamics of these alloys, their decomposition kinetics, and microstructure formation taking into account disorder of magnetic moments with temperature. We review modern theoretical tools which allow a consistent description of the electronic structure and energetics of random alloys with local magnetic moments that become totally or partially disordered when temperature increases. This approach gives a basis for an accurate finite-temperature description of alloys by calculating all the relevant contributions to the Gibbs energy from first-principles, including a configurational part as well as terms due to electronic, vibrational, and magnetic excitations. Applications of these theoretical approaches to the calculations of thermodynamics parameters at elevated temperatures (solution energies and effective interatomic interactions) are discussed including atomistic modeling of decomposition/clustering in Fe-based alloys. It provides a solid basis for understanding experimental data and for developing new steels for modern applications. The precipitation in Fe-Cu based alloys, the decomposition in Fe-Cr, and the short-range order formation in iron alloys with s-p elements are considered as examples.
Decomposition and aromatization of ethanol on ZSM-based catalysts.
Barthos, R; Széchenyi, A; Solymosi, F
2006-11-02
The adsorption, desorption, and reactions of ethanol have been investigated on pure and promoted ZSM-5 catalysts. FTIR spectroscopy indicated the formation of a strongly bonded ethoxy species on ZSM-5(80) at 300 K. TPD experiments following the adsorption of ethanol on both ZSM-5 and Mo2C/ZSM-5 have shown desorption profiles corresponding to unreacted ethanol and decomposition products (H2O, H2, CH3CHO, C4H10O, and C2H4). The main reaction pathway of ethanol on pure ZSM-5 is the dehydration reaction yielding ethylene, small amounts of hydrocarbons, and aromatics. Deposition of different additives, such as Mo2C, ZnO, and Ga2O3 on zeolite, greatly promoted the formation of benzene and toluene at 773-973 K, very likely by catalyzing the aromatization of ethylene formed in the dehydration process of ethanol. Separate studies of the reaction of ethylene revealed that the previous additives markedly enhanced the selectivity and the yield of aromatics on ZSM-5.
Iterative filtering decomposition based on local spectral evolution kernel
Wang, Yang; Wei, Guo-Wei; Yang, Siyang
2011-01-01
The synthesizing information, achieving understanding, and deriving insight from increasingly massive, time-varying, noisy and possibly conflicting data sets are some of most challenging tasks in the present information age. Traditional technologies, such as Fourier transform and wavelet multi-resolution analysis, are inadequate to handle all of the above-mentioned tasks. The empirical model decomposition (EMD) has emerged as a new powerful tool for resolving many challenging problems in data processing and analysis. Recently, an iterative filtering decomposition (IFD) has been introduced to address the stability and efficiency problems of the EMD. Another data analysis technique is the local spectral evolution kernel (LSEK), which provides a near prefect low pass filter with desirable time-frequency localizations. The present work utilizes the LSEK to further stabilize the IFD, and offers an efficient, flexible and robust scheme for information extraction, complexity reduction, and signal and image understanding. The performance of the present LSEK based IFD is intensively validated over a wide range of data processing tasks, including mode decomposition, analysis of time-varying data, information extraction from nonlinear dynamic systems, etc. The utility, robustness and usefulness of the proposed LESK based IFD are demonstrated via a large number of applications, such as the analysis of stock market data, the decomposition of ocean wave magnitudes, the understanding of physiologic signals and information recovery from noisy images. The performance of the proposed method is compared with that of existing methods in the literature. Our results indicate that the LSEK based IFD improves both the efficiency and the stability of conventional EMD algorithms. PMID:22350559
Motion Mode Decomposition Based on Discrete Fourier Series Expansion
NASA Astrophysics Data System (ADS)
Hatta, Yoshiyuki; Shimono, Tomoyuki
In recent years, several methods for decomposing the whole motion of a parallel multi-degrees-of-freedom (MDOF) system into motion modes have been proposed. A motion mode is a motion element that corresponds to a specific physical action, such as grasping, manipulating, and rotating. Modal decomposition is effective for the expression and analysis of a complicated motion. However, conventional methods can extract motion modes only if the arrangement of actuators in the system has spatial linearity and symmetry. Therefore, the actuators cannot be arranged arbitrarily when the conventional methods are applied. In order to solve this problem, a novel method for modal decomposition is proposed; this method is based on the discrete Fourier series expansion. The proposed method is applied to a parallel MDOF bilateral system in which the arrangement of actuators is spatially asymmetric. Finally, the validity of the proposed method is confirmed on the basis of the experimental results.
Liu, C Tony; Maxwell, Christopher I; Edwards, David R; Neverov, Alexei A; Mosey, Nicholas J; Brown, R Stan
2010-11-24
The methanolytic cleavage of a series of O,O-dimethyl O-aryl phosphorothioates (1a−g) catalyzed by a C,N-palladacycle, (2-[N,N-dimethylamino(methyl)phenyl]-C1,N)(pyridine) palladium(II) triflate (3), at 25 °C and sspH 11.7 in methanol is reported, along with data for the methanolytic cleavage of 1a−g. The methoxide reaction gives a linear log k2−OMe vs sspKa (phenol leaving group) Brønsted plot having a gradient of βlg = −0.47 ± 0.03, suggesting about 34% cleavage of the P−OAr bond in the transition state. On the other hand, the 3-catalyzed cleavage of 1 gives a Brønsted plot with a downward break at sspKa (phenol) 13, signifying a change in the rate-limiting step in the catalyzed reaction, with the two wings having βlg values of 0.0 ± 0.03 and −1.93 ± 0.06. The rate-limiting step for good substrates with low leaving group sspKa values is proposed to be substrate/pyridine exchange on the palladacycle, while for substrates with poor leaving groups, the rate-limiting step is a chemical one with extensive cleavage of the P−OAr bond. DFT calculations support this process and also identify two intermediates, namely, one where substrate/pyridine interchange has occurred to give the palladacycle coordinated to substrate through the S═P linkage and to methoxide (6) and another where intramolecular methoxide attack has occurred on the P═S unit to give a five-coordinate phosphorane (7) doubly coordinated to Pd via the S− and through a bridging methoxide linked to P and Pd. Attempts to identify the existence of the phosphorane by 31P NMR in a d4-methanol solution containing 10 mM each of 3, trimethyl phosphorothioate (a very slow cleaving substrate), and methoxide proved unsuccessful, instead showing that the phosphorothioate was slowly converted to trimethyl phosphate, with the palladacycle decomposing to Pd0 and free pyridine. These results provide the first reported example where a palladacycle-promoted solvolysis reaction exhibits a break in
Constrained reduced-order models based on proper orthogonal decomposition
Reddy, Sohail R.; Freno, Brian Andrew; Cizmas, Paul G. A.; ...
2017-04-09
A novel approach is presented to constrain reduced-order models (ROM) based on proper orthogonal decomposition (POD). The Karush–Kuhn–Tucker (KKT) conditions were applied to the traditional reduced-order model to constrain the solution to user-defined bounds. The constrained reduced-order model (C-ROM) was applied and validated against the analytical solution to the first-order wave equation. C-ROM was also applied to the analysis of fluidized beds. Lastly, it was shown that the ROM and C-ROM produced accurate results and that C-ROM was less sensitive to error propagation through time than the ROM.
Frequency Response of Multipoint Chemical Shift Based Spectral Decomposition
Brodsky, Ethan K.; Chebrolu, Venkata V.; Block, Walter F.; Reeder, Scott B.
2010-01-01
PURPOSE To provide a framework for characterizing the frequency response of multi-point chemical shift based species separation techniques. MATERIALS AND METHODS Multi-point chemical shift based species separation techniques acquire complex images at multiple echo times and perform maximum likelihood estimation to decompose signal from different species into separate images. In general, after a non-linear process of estimating and demodulating the field map, these decomposition methods are linear transforms from the echo-time domain to the chemical-shift-frequency domain, analogous to the Discrete Fourier Transform (DFT). In this work, we describe a technique for finding the magnitude and phase of chemical shift decomposition for input signals over a range of frequencies using numerical and experimental modeling and examine several important cases of species separation. RESULTS Simple expressions can be derived to describe the response to a wide variety of input signals. Agreement between numerical modeling and experimental results is very good. CONCLUSION Chemical shift based species separation is linear, and therefore can be fully described by the magnitude and phase curves of the frequency response. The periodic nature of the frequency response has important implications for the robustness of various techniques for resolving ambiguities in field inhomogeneity. PMID:20882625
Wavelet decomposition-based efficient face liveness detection
NASA Astrophysics Data System (ADS)
Moniruzzaman, Md.; Alam, Mohammad S.
2016-04-01
Existing face recognition systems are susceptible to spoofing attacks. So, Face liveness detection is a pivotal part for reliable face recognition, which has recently acknowledged vast attention. In this paper we propose a wavelet decomposition based face liveness recognition system using an energy calculation technique. Live faces contain high energy components compared to fake or printed image. In this paper, we calculate energy components of live face as well as fake face using discrete wavelet decomposition method. We analyze percentage of energy at different levels as well as for different wavelet basis function. We also analyze percentage of energy at different RGB bands and efficient face liveness detection method has been proposed. Discrete wavelet representation has been used to calculate decomposed energy components. Moreover, it provides differentiation of several spatial orientations as well as average and detailed information which are missing in the fake faces. This technique provides excellent discrimination capability when compared to the previously reported works based on the discrete Fourier transform and n-dimensional Fourier transform operations. To verify the proposed approach, we tested the performance using various face antispoofing datasets such as university of south Alabama (UFAD), and MSU face antispoofing dataset which incorporates different types of attacks. The test results obtained using the proposed technique shows better performance compared to existing techniques.
Kinetics of acid base catalyzed transesterification of Jatropha curcas oil.
Jain, Siddharth; Sharma, M P
2010-10-01
Out of various non-edible oil resources, Jatropha curcas oil (JCO) is considered as future feedstock for biodiesel production in India. Limited work is reported on the kinetics of transesterification of high free fatty acids containing oil. The present study reports the results of kinetic study of two-step acid base catalyzed transesterification process carried out at an optimum temperature of 65 °C and 50 °C for esterification and transesterification respectively under the optimum methanol to oil ratio of 3:7 (v/v), catalyst concentration 1% (w/w) for H₂SO₄ and NaOH. The yield of methyl ester (ME) has been used to study the effect of different parameters. The results indicate that both esterification and transesterification reaction are of first order with reaction rate constant of 0.0031 min⁻¹ and 0.008 min⁻¹ respectively. The maximum yield of 21.2% of ME during esterification and 90.1% from transesterification of pretreated JCO has been obtained.
Process Intensification in Base-Catalyzed Biodiesel Production
McFarlane, Joanna; Birdwell Jr, Joseph F; Tsouris, Costas; Jennings, Hal L
2008-01-01
Biodiesel is considered a means to diversify our supply of transportation fuel, addressing the goal of reducing our dependence on oil. Recent interest has resulted in biodiesel manufacture becoming more widely undertaken by commercial enterprises that are interested in minimizing the cost of feedstock materials and waste production, as well as maximizing the efficiency of production. Various means to accelerate batch processing have been investigated. Oak Ridge National Laboratory has experience in developing process intensification methods for nuclear separations, and this paper will discuss how technologies developed for very different applications have been modified for continuous reaction/separation of biodiesel. In collaboration with an industrial partner, this work addresses the aspect of base-catalyzed biodiesel production that limits it to a slow batch process. In particular, we have found that interfacial mass transfer and phase separation control the transesterification process and have developed a continuous two-phase reactor for online production of a methyl ester and glycerol. Enhancing the mass transfer has additional benefits such as being able to use an alcohol-to-oil phase ratio closer to stoichiometric than in conventional processing, hence minimizing the amount of solvent that has to be recycled and reducing post-processing clean up costs. Various technical issues associated with the application of process intensification technology will be discussed, including scale-up from the laboratory to a pilot-scale undertaking.
Distributed Damage Estimation for Prognostics based on Structural Model Decomposition
NASA Technical Reports Server (NTRS)
Daigle, Matthew; Bregon, Anibal; Roychoudhury, Indranil
2011-01-01
Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.
NASA Astrophysics Data System (ADS)
Mehedi, H.-A.; Baudrillart, B.; Alloyeau, D.; Mouhoub, O.; Ricolleau, C.; Pham, V. D.; Chacon, C.; Gicquel, A.; Lagoute, J.; Farhat, S.
2016-08-01
This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700-850 °C), molar concentration of methane (2%-20%), growth time (30-90 s), and microwave power (300-400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline quality and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2-7 high quality graphene layers.
Mehedi, H.-A.; Baudrillart, B.; Gicquel, A.; Farhat, S.; Alloyeau, D.; Mouhoub, O.; Ricolleau, C.; Pham, V. D.; Chacon, C.; Lagoute, J.
2016-08-14
This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700–850 °C), molar concentration of methane (2%–20%), growth time (30–90 s), and microwave power (300–400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline quality and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2–7 high quality graphene layers.
FCDECOMP: decomposition of metabolic networks based on flux coupling relations.
Rezvan, Abolfazl; Marashi, Sayed-Amir; Eslahchi, Changiz
2014-10-01
A metabolic network model provides a computational framework to study the metabolism of a cell at the system level. Due to their large sizes and complexity, rational decomposition of these networks into subsystems is a strategy to obtain better insight into the metabolic functions. Additionally, decomposing metabolic networks paves the way to use computational methods that will be otherwise very slow when run on the original genome-scale network. In the present study, we propose FCDECOMP decomposition method based on flux coupling relations (FCRs) between pairs of reaction fluxes. This approach utilizes a genetic algorithm (GA) to obtain subsystems that can be analyzed in isolation, i.e. without considering the reactions of the original network in the analysis. Therefore, we propose that our method is useful for discovering biologically meaningful modules in metabolic networks. As a case study, we show that when this method is applied to the metabolic networks of barley seeds and yeast, the modules are in good agreement with the biological compartments of these networks.
Pseudo-spectral reverse time migration based on wavefield decomposition
NASA Astrophysics Data System (ADS)
Du, Zengli; Liu, Jianjun; Xu, Feng; Li, Yongzhang
2017-02-01
The accuracy of seismic numerical simulations and the effectiveness of imaging conditions are important in reverse time migration studies. Using the pseudo-spectral method, the precision of the calculated spatial derivative of the seismic wavefield can be improved, increasing the vertical resolution of images. Low-frequency background noise, generated by the zero-lag cross-correlation of mismatched forward-propagated and backward-propagated wavefields at the impedance interfaces, can be eliminated effectively by using the imaging condition based on the wavefield decomposition technique. The computation complexity can be reduced when imaging is performed in the frequency domain. Since the Fourier transformation in the z-axis may be derived directly as one of the intermediate results of the spatial derivative calculation, the computation load of the wavefield decomposition can be reduced, improving the computation efficiency of imaging. Comparison of the results for a pulse response in a constant-velocity medium indicates that, compared with the finite difference method, the peak frequency of the Ricker wavelet can be increased by 10-15 Hz for avoiding spatial numerical dispersion, when the second-order spatial derivative of the seismic wavefield is obtained using the pseudo-spectral method. The results for the SEG/EAGE and Sigsbee2b models show that the signal-to-noise ratio of the profile and the imaging quality of the boundaries of the salt dome migrated using the pseudo-spectral method are better than those obtained using the finite difference method.
Pseudospectral reverse time migration based on wavefield decomposition
NASA Astrophysics Data System (ADS)
Du, Zengli; Liu, Jianjun; Xu, Feng; Li, Yongzhang
2017-05-01
The accuracy of seismic numerical simulations and the effectiveness of imaging conditions are important in reverse time migration studies. Using the pseudospectral method, the precision of the calculated spatial derivative of the seismic wavefield can be improved, increasing the vertical resolution of images. Low-frequency background noise, generated by the zero-lag cross-correlation of mismatched forward-propagated and backward-propagated wavefields at the impedance interfaces, can be eliminated effectively by using the imaging condition based on the wavefield decomposition technique. The computation complexity can be reduced when imaging is performed in the frequency domain. Since the Fourier transformation in the z-axis may be derived directly as one of the intermediate results of the spatial derivative calculation, the computation load of the wavefield decomposition can be reduced, improving the computation efficiency of imaging. Comparison of the results for a pulse response in a constant-velocity medium indicates that, compared with the finite difference method, the peak frequency of the Ricker wavelet can be increased by 10-15 Hz for avoiding spatial numerical dispersion, when the second-order spatial derivative of the seismic wavefield is obtained using the pseudospectral method. The results for the SEG/EAGE and Sigsbee2b models show that the signal-to-noise ratio of the profile and the imaging quality of the boundaries of the salt dome migrated using the pseudospectral method are better than those obtained using the finite difference method.
Tensor decomposition and nonlocal means based spectral CT reconstruction
NASA Astrophysics Data System (ADS)
Zhang, Yanbo; Yu, Hengyong
2016-10-01
As one of the state-of-the-art detectors, photon counting detector is used in spectral CT to classify the received photons into several energy channels and generate multichannel projection simultaneously. However, the projection always contains severe noise due to the low counts in each energy channel. How to reconstruct high-quality images from photon counting detector based spectral CT is a challenging problem. It is widely accepted that there exists self-similarity over the spatial domain in a CT image. Moreover, because a multichannel CT image is obtained from the same object at different energy, images among channels are highly correlated. Motivated by these two characteristics of the spectral CT, we employ tensor decomposition and nonlocal means methods for spectral CT iterative reconstruction. Our method includes three basic steps. First, each channel image is updated by using the OS-SART. Second, small 3D volumetric patches (tensor) are extracted from the multichannel image, and higher-order singular value decomposition (HOSVD) is performed on each tensor, which can help to enhance the spatial sparsity and spectral correlation. Third, in order to employ the self-similarity in CT images, similar patches are grouped to reduce noise using the nonlocal means method. These three steps are repeated alternatively till the stopping criteria are met. The effectiveness of the developed algorithm is validated on both numerically simulated and realistic preclinical datasets. Our results show that the proposed method achieves promising performance in terms of noise reduction and fine structures preservation.
Recurrence quantity analysis based on singular value decomposition
NASA Astrophysics Data System (ADS)
Bian, Songhan; Shang, Pengjian
2017-05-01
Recurrence plot (RP) has turned into a powerful tool in many different sciences in the last three decades. To quantify the complexity and structure of RP, recurrence quantification analysis (RQA) has been developed based on the measures of recurrence density, diagonal lines, vertical lines and horizontal lines. This paper will study the RP based on singular value decomposition which is a new perspective of RP study. Principal singular value proportion (PSVP) will be proposed as one new RQA measure and bigger PSVP means higher complexity for one system. In contrast, smaller PSVP reflects a regular and stable system. Considering the advantage of this method in detecting the complexity and periodicity of systems, several simulation and real data experiments are chosen to examine the performance of this new RQA.
Automatic classification of visual evoked potentials based on wavelet decomposition
NASA Astrophysics Data System (ADS)
Stasiakiewicz, Paweł; Dobrowolski, Andrzej P.; Tomczykiewicz, Kazimierz
2017-04-01
Diagnosis of part of the visual system, that is responsible for conducting compound action potential, is generally based on visual evoked potentials generated as a result of stimulation of the eye by external light source. The condition of patient's visual path is assessed by set of parameters that describe the time domain characteristic extremes called waves. The decision process is compound therefore diagnosis significantly depends on experience of a doctor. The authors developed a procedure - based on wavelet decomposition and linear discriminant analysis - that ensures automatic classification of visual evoked potentials. The algorithm enables to assign individual case to normal or pathological class. The proposed classifier has a 96,4% sensitivity at 10,4% probability of false alarm in a group of 220 cases and area under curve ROC equals to 0,96 which, from the medical point of view, is a very good result.
Automated Decomposition of Model-based Learning Problems
NASA Technical Reports Server (NTRS)
Williams, Brian C.; Millar, Bill
1996-01-01
A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.
Automated Decomposition of Model-based Learning Problems
NASA Technical Reports Server (NTRS)
Williams, Brian C.; Millar, Bill
1996-01-01
A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.
Alcaide, Benito; Almendros, Pedro; Alonso, José M
2011-09-13
The last decade has witnessed dramatic growth in the number of reactions catalyzed by gold complexes because of their powerful soft Lewis acid nature. In particular, the gold-catalyzed activation of propargylic compounds has progressively emerged in recent years. Some of these gold-catalyzed reactions in alkynes have been optimized and show significant utility in organic synthesis. Thus, apart from significant methodology work, in the meantime gold-catalyzed cyclizations in alkynol derivatives have become an efficient tool in total synthesis. However, there is a lack of specific review articles covering the joined importance of both gold salts and alkynol-based compounds for the synthesis of natural products and derivatives. The aim of this Review is to survey the chemistry of alkynol derivatives under gold-catalyzed cyclization conditions and its utility in total synthesis, concentrating on the advances that have been made in the last decade, and in particular in the last quinquennium.
Major, Terry C.; Brant, David O.; Burney, Charles P.; Amoako, Kagya A.; Annich, Gail M.; Meyerhoff, Mark E.; Handa, Hitesh; Bartlett, Robert H.
2011-01-01
Nitric oxide (NO) generating (NOGen) materials have been shown previously to create localized increases in NO concentration by the catalytic decomposition of blood S-nitrosothiols (RSNO) via copper (Cu)-containing polymer coatings and may improve extracorporeal circulation (ECC) hemocompatibility. In this work, a NOGen polymeric coating composed of a Cuo-nanoparticle (80 nm)-containing hydrophilic polyurethane (SP-60D-60) combined with the intravenous infusion of an RSNO, S-nitroso-N-acetylpenicillamine (SNAP), is evaluated in a 4 h rabbit thrombogenicity model and the anti-thrombotic mechanism is investigated. Polymer films containing 10 wt.% Cuo-nanoparticles coated on the inner walls of ECC circuits are employed concomitantly with systemic SNAP administration (0.1182 μmol/kg/min) to yield significantly reduced ECC thrombus formation compared to polymer control + systemic SNAP or 10 wt.% Cu NOGen + systemic saline after 4 h blood exposure (0.4 ± 0.2 NOGen/SNAP vs 4.9 ± 0.5 control/SNAP or 3.2 ± 0.2 pixels/cm2 NOGen/saline). Platelet count (3.9 ± 0.7 NOGen/SNAP vs 1.8 ± 0.1 control/SNAP or 3.0 ± 0.2 × 108/ml NOGen/saline) and plasma fibrinogen levels were preserved after 4 h blood exposure with the NOGen/SNAP combination vs either the control/SNAP or the NOGen/saline groups. Platelet function as measured by aggregometry (51 ± 9 NOGen/SNAP vs 49 ± 3% NOGen/saline) significantly decreased in both the NOGen/SNAP and NOGen/saline groups while platelet P-selectin mean fluorescence intensity (MFI) as measured by flow cytometry was not decreased after 4 h on ECC to ex vivo collagen stimulation (26 ± 2 NOGen/SNAP vs 29 ± 1 MFI baseline). Western blotting showed that fibrinogen activation as assessed by Aγ dimer expression was reduced after 4 h on ECC with NOGen/SNAP (68 ± 7 vs 83 ± 3% control/SNAP). These results suggest that the NOGen polymer coating combined with SNAP infusion preserves platelets in blood exposure to ECCs by attenuating activated
Quantum Image Encryption Algorithm Based on Image Correlation Decomposition
NASA Astrophysics Data System (ADS)
Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun
2015-02-01
A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.
Catalyzed sodium chlorate candles
NASA Technical Reports Server (NTRS)
Malich, C. W.; Wydeven, T.
1972-01-01
The catalytic effect of cobalt powder on chlorate decomposition has been confirmed. Catalysis is enhanced by oxidation of the metal during burning. Catalysts other than cobalt compounds should also be effective; the complete elimination of fuel has shown that the oxidation of cobalt during decomposition is not a vital factor in the improved performance of catalyzed candles.
NASA Astrophysics Data System (ADS)
Jordi, Antoni; Georgas, Nickitas; Blumberg, Alan
2017-05-01
This paper presents a new parallel domain decomposition algorithm based on integer linear programming (ILP), a mathematical optimization method. To minimize the computation time of coastal ocean circulation models, the ILP decomposition algorithm divides the global domain in local domains with balanced work load according to the number of processors and avoids computations over as many as land grid cells as possible. In addition, it maintains the use of logically rectangular local domains and achieves the exact same results as traditional domain decomposition algorithms (such as Cartesian decomposition). However, the ILP decomposition algorithm may not converge to an exact solution for relatively large domains. To overcome this problem, we developed two ILP decomposition formulations. The first one (complete formulation) has no additional restriction, although it is impractical for large global domains. The second one (feasible) imposes local domains with the same dimensions and looks for the feasibility of such decomposition, which allows much larger global domains. Parallel performance of both ILP formulations is compared to a base Cartesian decomposition by simulating two cases with the newly created parallel version of the Stevens Institute of Technology's Estuarine and Coastal Ocean Model (sECOM). Simulations with the ILP formulations run always faster than the ones with the base decomposition, and the complete formulation is better than the feasible one when it is applicable. In addition, parallel efficiency with the ILP decomposition may be greater than one.
Identifying key nodes in multilayer networks based on tensor decomposition
NASA Astrophysics Data System (ADS)
Wang, Dingjie; Wang, Haitao; Zou, Xiufen
2017-06-01
The identification of essential agents in multilayer networks characterized by different types of interactions is a crucial and challenging topic, one that is essential for understanding the topological structure and dynamic processes of multilayer networks. In this paper, we use the fourth-order tensor to represent multilayer networks and propose a novel method to identify essential nodes based on CANDECOMP/PARAFAC (CP) tensor decomposition, referred to as the EDCPTD centrality. This method is based on the perspective of multilayer networked structures, which integrate the information of edges among nodes and links between different layers to quantify the importance of nodes in multilayer networks. Three real-world multilayer biological networks are used to evaluate the performance of the EDCPTD centrality. The bar chart and ROC curves of these multilayer networks indicate that the proposed approach is a good alternative index to identify real important nodes. Meanwhile, by comparing the behavior of both the proposed method and the aggregated single-layer methods, we demonstrate that neglecting the multiple relationships between nodes may lead to incorrect identification of the most versatile nodes. Furthermore, the Gene Ontology functional annotation demonstrates that the identified top nodes based on the proposed approach play a significant role in many vital biological processes. Finally, we have implemented many centrality methods of multilayer networks (including our method and the published methods) and created a visual software based on the MATLAB GUI, called ENMNFinder, which can be used by other researchers.
NASA Astrophysics Data System (ADS)
Xiang, Deliang; Tang, Tao; Ban, Yifang; Su, Yi; Kuang, Gangyao
2016-06-01
Since it has been validated that cross-polarized scattering (HV) is caused not only by vegetation but also by rotated dihedrals, in this study, we use rotated dihedral corner reflectors to form a cross scattering matrix and propose an extended four-component model-based decomposition method for PolSAR data over urban areas. Unlike other urban area decomposition techniques which need to discriminate the urban and natural areas before decomposition, this proposed method is applied on PolSAR image directly. The building orientation angle is considered in this scattering matrix, making it flexible and adaptive in the decomposition. Therefore, we can separate cross scattering of urban areas from the overall HV component. Further, the cross and helix scattering components are also compared. Then, using these decomposed scattering powers, the buildings and natural areas can be easily discriminated from each other using a simple unsupervised K-means classifier. Moreover, buildings aligned and not aligned along the radar flight direction can be also distinguished clearly. Spaceborne RADARSAT-2 and airborne AIRSAR full polarimetric SAR data are used to validate the performance of our proposed method. The cross scattering power of oriented buildings is generated, leading to a better decomposition result for urban areas with respect to other state-of-the-art urban decomposition techniques. The decomposed scattering powers significantly improve the classification accuracy for urban areas.
Decomposition-based transfer distance metric learning for image classification.
Luo, Yong; Liu, Tongliang; Tao, Dacheng; Xu, Chao
2014-09-01
Distance metric learning (DML) is a critical factor for image analysis and pattern recognition. To learn a robust distance metric for a target task, we need abundant side information (i.e., the similarity/dissimilarity pairwise constraints over the labeled data), which is usually unavailable in practice due to the high labeling cost. This paper considers the transfer learning setting by exploiting the large quantity of side information from certain related, but different source tasks to help with target metric learning (with only a little side information). The state-of-the-art metric learning algorithms usually fail in this setting because the data distributions of the source task and target task are often quite different. We address this problem by assuming that the target distance metric lies in the space spanned by the eigenvectors of the source metrics (or other randomly generated bases). The target metric is represented as a combination of the base metrics, which are computed using the decomposed components of the source metrics (or simply a set of random bases); we call the proposed method, decomposition-based transfer DML (DTDML). In particular, DTDML learns a sparse combination of the base metrics to construct the target metric by forcing the target metric to be close to an integration of the source metrics. The main advantage of the proposed method compared with existing transfer metric learning approaches is that we directly learn the base metric coefficients instead of the target metric. To this end, far fewer variables need to be learned. We therefore obtain more reliable solutions given the limited side information and the optimization tends to be faster. Experiments on the popular handwritten image (digit, letter) classification and challenge natural image annotation tasks demonstrate the effectiveness of the proposed method.
Singular Value Decomposition-based Alternative Splicing Detection
Hu, Jianhua; He, Xuming; Cote, Gilbert J.; Krahe, Ralf
2009-01-01
SUMMARY Altered alternative splicing has been identified as an important factor in tumorigenesis. The Affymetrix exon tiling array is designed for detecting alternative splicing events in a transcriptome-wide fashion; however, there are currently few analysis tools that are well studied for effective detection of alternative splicing events. We propose a new screening procedure based on singular value decomposition (SVD) of the residual matrix from a robust additive model fit to probe selection region (PSR) data. With this approach, we analyze the exon tiling array data from a brain cancer study conducted at the M. D. Anderson Cancer Center, and show that the proposed SVD-based approach is able to better accommodate outlying measures and capitalize on the multidimensional group-by-PSR gene expression profiles for more effective detection of group-specific alternative splicing events as well as the PSRs that are most likely associated with the alternative splicing. Lab validation confirmed some of our findings, but the list of candidates detected with our proposed method may provide a better signpost to guide further investigations. PMID:20305737
NASA Astrophysics Data System (ADS)
Zhao, Weichen; Sun, Zhuo; Kong, Song
2016-10-01
Wireless devices can be identified by the fingerprint extracted from the signal transmitted, which is useful in wireless communication security and other fields. This paper presents a method that extracts fingerprint based on phase noise of signal and multiple level wavelet decomposition. The phase of signal will be extracted first and then decomposed by multiple level wavelet decomposition. The statistic value of each wavelet coefficient vector is utilized for constructing fingerprint. Besides, the relationship between wavelet decomposition level and recognition accuracy is simulated. And advertised decomposition level is revealed as well. Compared with previous methods, our method is simpler and the accuracy of recognition remains high when Signal Noise Ratio (SNR) is low.
Analysis of Visual Illusions Using Multiresolution Wavelet Decomposition Based Models
1991-12-01
that finds the projection of the include image onto the space Wm, orthogonal to the Vm space where m is the current level of decompostion . It generates...the same session as the Reconstruction as long as the Decompostion was run in a prior session and the files still reside in the current directory. An...Decomposition portion. But, it is not necessary to run the Decomposition during the same session as the Reconstruction as long as the Decompostion was
Accurate tempo estimation based on harmonic + noise decomposition
NASA Astrophysics Data System (ADS)
Alonso, Miguel; Richard, Gael; David, Bertrand
2006-12-01
We present an innovative tempo estimation system that processes acoustic audio signals and does not use any high-level musical knowledge. Our proposal relies on a harmonic + noise decomposition of the audio signal by means of a subspace analysis method. Then, a technique to measure the degree of musical accentuation as a function of time is developed and separately applied to the harmonic and noise parts of the input signal. This is followed by a periodicity estimation block that calculates the salience of musical accents for a large number of potential periods. Next, a multipath dynamic programming searches among all the potential periodicities for the most consistent prospects through time, and finally the most energetic candidate is selected as tempo. Our proposal is validated using a manually annotated test-base containing 961 music signals from various musical genres. In addition, the performance of the algorithm under different configurations is compared. The robustness of the algorithm when processing signals of degraded quality is also measured.
Problem decomposition and domain-based parallelism via group theoretic principles
Makai, M.; Orechwa, Y.
1997-10-01
A systematic approach based on group theoretic principles, is presented for the decomposition of the solution algorithm of boundary value problems specified over symmetric domains, which is amenable to implementation for parallel computation. The principles are applied to the linear transport equation in general, and the decomposition is demonstrated for a square node in particular.
NASA Technical Reports Server (NTRS)
Behrens, R.; Minier, L.
1998-01-01
The thermal decomposition of ammonium perchlorate (AP) and ammonium-perchlorate-based composite propellants is studied using the simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) technique. The main objective of the present work is to evaluate whether the STMBMS can provide new data on these materials that will have sufficient detail on the reaction mechanisms and associated reaction kinetics to permit creation of a detailed model of the thermal decomposition process. Such a model is a necessary ingredient to engineering models of ignition and slow-cookoff for these AP-based composite propellants. Results show that the decomposition of pure AP is controlled by two processes. One occurs at lower temperatures (240 to 270 C), produces mainly H2O, O2, Cl2, N2O and HCl, and is shown to occur in the solid phase within the AP particles. 200(micro) diameter AP particles undergo 25% decomposition in the solid phase, whereas 20(micro) diameter AP particles undergo only 13% decomposition. The second process is dissociative sublimation of AP to NH3 + HClO4 followed by the decomposition of, and reaction between, these two products in the gas phase. The dissociative sublimation process occurs over the entire temperature range of AP decomposition, but only becomes dominant at temperatures above those for the solid-phase decomposition. AP-based composite propellants are used extensively in both small tactical rocket motors and large strategic rocket systems.
Behrens, R.; Minier, L.
1998-03-24
The thermal decomposition of ammonium perchlorate (AP) and ammonium-perchlorate-based composite propellants is studied using the simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) technique. The main objective of the present work is to evaluate whether the STMBMS can provide new data on these materials that will have sufficient detail on the reaction mechanisms and associated reaction kinetics to permit creation of a detailed model of the thermal decomposition process. Such a model is a necessary ingredient to engineering models of ignition and slow-cookoff for these AP-based composite propellants. Results show that the decomposition of pure AP is controlled by two processes. One occurs at lower temperatures (240 to 270 C), produces mainly H{sub 2}O, O{sub 2}, Cl{sub 2}, N{sub 2}O and HCl, and is shown to occur in the solid phase within the AP particles. 200{micro} diameter AP particles undergo 25% decomposition in the solid phase, whereas 20{micro} diameter AP particles undergo only 13% decomposition. The second process is dissociative sublimation of AP to NH{sub 3} + HClO{sub 4} followed by the decomposition of, and reaction between, these two products in the gas phase. The dissociative sublimation process occurs over the entire temperature range of AP decomposition, but only becomes dominant at temperatures above those for the solid-phase decomposition. AP-based composite propellants are used extensively in both small tactical rocket motors and large strategic rocket systems.
Statistical Analysis of the Ionosphere based on Singular Value Decomposition
NASA Astrophysics Data System (ADS)
Demir, Uygar; Arikan, Feza; Necat Deviren, M.; Toker, Cenk
2016-07-01
Ionosphere is made up of a spatio-temporally varying trend structure and secondary variations due to solar, geomagnetic, gravitational and seismic activities. Hence, it is important to monitor the ionosphere and acquire up-to-date information about its state in order both to better understand the physical phenomena that cause the variability and also to predict the effect of the ionosphere on HF and satellite communications, and satellite-based positioning systems. To charaterise the behaviour of the ionosphere, we propose to apply Singular Value Decomposition (SVD) to Total Electron Content (TEC) maps obtained from the TNPGN-Active (Turkish National Permanent GPS Network) CORS network. TNPGN-Active network consists of 146 GNSS receivers spread over Turkey. IONOLAB-TEC values estimated from each station are spatio-temporally interpolated using a Universal Kriging based algorithm with linear trend, namely IONOLAB-MAP, with very high spatial resolution. It is observed that the dominant singular value of TEC maps is an indicator of the trend structure of the ionosphere. The diurnal, seasonal and annual variability of the most dominant value is the representation of solar effect on ionosphere in midlatitude range. Secondary and smaller singular values are indicators of secondary variation which can have significance especially during geomagnetic storms or seismic disturbances. The dominant singular values are related to the physical basis vectors where ionosphere can be fully reconstructed using these vectors. Therefore, the proposed method can be used both for the monitoring of the current state of a region and also for the prediction and tracking of future states of ionosphere using singular values and singular basis vectors. This study is supported by by TUBITAK 115E915 and Joint TUBITAK 114E092 and AS CR14/001 projects.
Terahertz Spectrum Analysis Based on Empirical Mode Decomposition
NASA Astrophysics Data System (ADS)
Su, Yunpeng; Zheng, Xiaoping; Deng, Xiaojiao
2017-08-01
Precise identification of terahertz absorption peaks for materials with low concentration and high attenuation still remains a challenge. Empirical mode decomposition was applied to terahertz spectrum analysis in order to improve the performance on spectral fingerprints identification. We conducted experiments on water vapor and carbon monoxide respectively with terahertz time domain spectroscopy. By comparing their absorption spectra before and after empirical mode decomposition, we demonstrated that the first-order intrinsic mode function shows absorption peaks clearly in high-frequency range. By comparing the frequency spectra of the sample signals and their intrinsic mode functions, we proved that the first-order function contains most of the original signal's energy and frequency information so that it cannot be left out or replaced by high-order functions in spectral fingerprints detection. Empirical mode decomposition not only acts as an effective supplementary means to terahertz time-domain spectroscopy but also shows great potential in discrimination of materials and prediction of their concentrations.
Decomposition-Based Decision Making for Aerospace Vehicle Design
NASA Technical Reports Server (NTRS)
Borer, Nicholas K.; Mavris, DImitri N.
2005-01-01
reader to observe how this technique can be applied to aerospace systems design and compare the results of this so-called Decomposition-Based Decision Making to more traditional design approaches.
Eigen-decomposition-based models for model OPC
NASA Astrophysics Data System (ADS)
Shi, Xuelong; Laidig, Thomas L.; Chen, J. Fung; Van Den Broeke, Douglas J.; Hsu, Stephen D.; Hsu, Michael; Wampler, Kurt E.; Hollerbach, Uwe
2004-08-01
Model based optical proximity correction (OPC) to enhance image fidelity and process robustness has become one of the most critical components that enable optical lithography tackling 45nm node and beyond. To meet the challenges imposed by the previously unthinkable low k1 for manufacturing with most stringent dimension control requirements, a capable model OPC to meet such an aggressive lithography challenges has been urgently called upon. In addition to providing better accuracy for the currently implemented process technologies, the new model OPC must work well with Chromeless Phase Lithography (CPL) in which the topography on the mask is rather significant, and Double Dipole Lithography (DDL) in which two masks and two exposures are needed. It must also be able to intelligently take into account the effect from the more aggressive illuminations, such as customer designed illuminator and experimental measured illuminator profile from the scanners. This capability is very important since the real illuminator pupil can impact OPC accuracy. The physical and mathematical foundation of the model must be well thought of to meet the requirement for the above-mentioned applications. We have developed a novel Eigen Decomposition Model (EDM) for model OPC treatment applicable for all types of advanced binary and phase-shifting masks. Together with a full 2D model calibration and verification methodology, the results from this new model OPC have proven to achieve a superb CD accuracy with versatile capabilities for extreme low k1 imaging application. This report will explain how the model works with example applications and actual wafer results.
An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation
Yan, Honghang; Deng, Fang; Sun, Jian; Chen, Jie
2014-01-01
In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition of N subparts and reduces the training time to 1N and memory cost to 1N, has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. PMID:25232912
Salloum, Maher N.; Gharagozloo, Patricia E.
2013-10-01
Metal particle beds have recently become a major technique for hydrogen storage. In order to extract hydrogen from such beds, it is crucial to understand the decomposition kinetics of the metal hydride. We are interested in obtaining a a better understanding of the uranium hydride (UH3) decomposition kinetics. We first developed an empirical model by fitting data compiled from different experimental studies in the literature and quantified the uncertainty resulting from the scattered data. We found that the decomposition time range predicted by the obtained kinetics was in a good agreement with published experimental results. Secondly, we developed a physics based mathematical model to simulate the rate of hydrogen diffusion in a hydride particle during the decomposition. We used this model to simulate the decomposition of the particles for temperatures ranging from 300K to 1000K while propagating parametric uncertainty and evaluated the kinetics from the results. We compared the kinetics parameters derived from the empirical and physics based models and found that the uncertainty in the kinetics predicted by the physics based model covers the scattered experimental data. Finally, we used the physics-based kinetics parameters to simulate the effects of boundary resistances and powder morphological changes during decomposition in a continuum level model. We found that the species change within the bed occurring during the decomposition accelerates the hydrogen flow by increasing the bed permeability, while the pressure buildup and the thermal barrier forming at the wall significantly impede the hydrogen extraction.
Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems
2008-04-01
bearing fault diagnosis – their effectiveness and flexibilities. Journal of Vibration and Acoustics July 2001, ASME. 3. Staszewski, W. J. Structural...Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems by Hiralal Khatri, Kenneth Ranney, Kwok Tom, and Romeo...Laboratory Adelphi, MD 20783-1197 ARL-TR-4301 April 2008 Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems
An effective diffusivity model based on Koopman mode decomposition
NASA Astrophysics Data System (ADS)
Arbabi, Hassan; Mezic, Igor
2016-11-01
In the previous work, we had shown that the Koopman mode decomposition (KMD) can be used to analyze mixing of passive tracers in time-dependent flows. In this talk, we discuss the extension of this type of analysis to the case of advection-diffusion transport for passive scalar fields. Application of KMD to flows with complex time-dependence yields a decomposition of the flow into mean, periodic and chaotic components. We briefly discuss the computation of these components using a combination of harmonic averaging and Discrete Fourier Transform. We propose a new effective diffusivity model in which the advection is dominated by mean and periodic components whereas the effect of chaotic motion is absorbed into an effective diffusivity tensor. The performance of this model is investigated in the case of lid-driven cavity flow.
Residential electricity load decomposition method based on maximum a posteriori probability
NASA Astrophysics Data System (ADS)
Shan, Guangpu; Zhou, Heng; Liu, Song; Liu, Peng
2017-05-01
In order to improvement problems that the computational complexity and the accuracy is not high in load decomposition, a load decomposition method based on the maximum a posteriori probability is proposed, the electrical equipment steady-state current is chosen as load characteristic, according to the Bayesian formula, all the electric equipment's' electricity information value can be acquired at a time exactly. Experimental results show that the method can identify the running state of each power equipment, and can get a higher decomposition accuracy. In addition, the data used can be collected by the common smart meters that can be directly got from the current market, reducing the cost of hardware input.
Jin, Xin; Jin, Pengkang; Hou, Rui; Yang, Lei; Wang, Xiaochang C
2017-04-05
A novel hybrid ozonation-coagulation (HOC) process was developed for application in wastewater reclamation. In this process, ozonation and coagulation occurred simultaneously within a single unit. Compared with the conventional pre-ozonation-coagulation process, the HOC process exhibited much better performance in removing dissolved organic matters. In particular, the maximal organic matters removal efficiency was obtained at the ozone dosage of 1mgO3/mg DOC at each pH value (pH 5, 7 and 9). In order to interpret the mechanism of the HOC process, ozone decomposition was monitored. The results indicated that ozone decomposed much faster in the HOC process. Moreover, by using the reagent of O3-resistant hydroxyl radical (OH) probe compound, para-chlorobenzoic acid (pCBA), and electron paramagnetic resonance (EPR) analysis, it was observed that the HOC process generated higher content of OH compared with pre-ozonation process. This indicates that the OH oxidation reaction as the key step can be catalyzed and enhanced by Al-based coagulants and their hydrolyzed products in this developed process. Thus, based on the catalytic effects of Al-based coagulants on ozonation, the HOC process provides a promising alternative to the conventional technology for wastewater reclamation in terms of higher efficiency. Copyright © 2016 Elsevier B.V. All rights reserved.
Image-based Material Decomposition with a General Volume Constraint for Photon-Counting CT.
Li, Zhoubo; Leng, Shuai; Yu, Lifeng; Yu, Zhicong; McCollough, Cynthia H
Photon-counting CT (PCCT) potentially offers both improved dose efficiency and material decomposition capabilities relative to CT systems using energy integrating detectors. With respect to material decomposition, both projection-based and image-based methods have been proposed, most of which require accurate a priori information regarding the shape of the x-ray spectra and the response of the detectors. Additionally, projection-based methods require access to projection data. These data can be difficult to obtain, since spectra, detector response, and projection data formats are proprietary information. Further, some published image-based, 3-material decomposition methods require a volume conservation assumption, which is often violated in solutions. We have developed an image-based material decomposition method that can overcome those limitations. We introduced a general condition on volume constraint that does not require the volume to be conserved in a mixture. An empirical calibration can be performed with various concentrations of basis materials. The material decomposition method was applied to images acquired from a prototype whole-body PCCT scanner. The results showed good agreement between the estimation and known mass concentration values. Factors affecting the performance of material decomposition, such as energy threshold configuration and volume conservation constraint, were also investigated. Changes in accuracy of the mass concentration estimates were demonstrated for four different energy configurations and when volume conservation was assumed.
Zhu, Bo; Yan, Lin; Pan, Yuanhang; Lee, Richmond; Liu, Hongjun; Han, Zhiqiang; Huang, Kuo-Wei; Tan, Choon-Hong; Jiang, Zhiyong
2011-08-19
A Lewis base catalyzed allylic hydroxylation of Morita-Baylis-Hillman (MBH) carbonates has been developed. Various chiral MBH alcohols can be synthesized in high yields (up to 99%) and excellent enantioselectivities (up to 94% ee). This is the first report using water as a nucleophile in asymmetric organocatalysis. The nucleophilic role of water has been verified using (18)O-labeling experiments.
Chung-Yun Hse
2009-01-01
To upgrade the performance of urea-formaldehyde (UF) resin bonded particleboards, melamine modified urea-formaldehyde (MUF) resins based on strong acidic pH catalyzed UF polymers were investigated. The study was conducted in a series of two experiments: 1) formulation of MUF resins based on a UF polymer catalyzed with strong acidic pH and 2) determination of the...
NASA Astrophysics Data System (ADS)
Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng
2017-08-01
Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.
Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes
NASA Astrophysics Data System (ADS)
Grigoryan, Artyom M.
2015-03-01
In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.
A knowledge-based tool for multilevel decomposition of a complex design problem
NASA Technical Reports Server (NTRS)
Rogers, James L.
1989-01-01
Although much work has been done in applying artificial intelligence (AI) tools and techniques to problems in different engineering disciplines, only recently has the application of these tools begun to spread to the decomposition of complex design problems. A new tool based on AI techniques has been developed to implement a decomposition scheme suitable for multilevel optimization and display of data in an N x N matrix format.
Base-Catalyzed Linkage Isomerization: An Undergraduate Inorganic Kinetics Experiment.
ERIC Educational Resources Information Center
Jackson, W. G.; And Others
1981-01-01
Describes kinetics experiments completed in a single two-hour laboratory period at 25 degrees Centigrade of nitrito to nitro rearrangement, based on the recently discovered base-catalysis path. Includes information on synthesis and characterization of linkage isomers, spectrophotometric techniques, and experimental procedures. (SK)
Base-Catalyzed Linkage Isomerization: An Undergraduate Inorganic Kinetics Experiment.
ERIC Educational Resources Information Center
Jackson, W. G.; And Others
1981-01-01
Describes kinetics experiments completed in a single two-hour laboratory period at 25 degrees Centigrade of nitrito to nitro rearrangement, based on the recently discovered base-catalysis path. Includes information on synthesis and characterization of linkage isomers, spectrophotometric techniques, and experimental procedures. (SK)
Base catalyzed synthesis of bicyclo[3.2.1]octane scaffolds.
Boehringer, Régis; Geoffroy, Philippe; Miesch, Michel
2015-07-07
The base-catalyzed reaction of achiral 1,3-cyclopentanediones tethered to activated olefins afforded in high yields bicyclo[3.2.1]octane-6,8-dione or bicyclo[3.2.1]octane-6-carboxylate derivatives bearing respectively three or five stereogenic centers. The course of the reaction is closely related to the reaction time and to the base involved in the reaction.
Asymmetric color image encryption based on singular value decomposition
NASA Astrophysics Data System (ADS)
Yao, Lili; Yuan, Caojin; Qiang, Junjie; Feng, Shaotong; Nie, Shouping
2017-02-01
A novel asymmetric color image encryption approach by using singular value decomposition (SVD) is proposed. The original color image is encrypted into a ciphertext shown as an indexed image by using the proposed method. The red, green and blue components of the color image are subsequently encoded into a complex function which is then separated into U, S and V parts by SVD. The data matrix of the ciphertext is obtained by multiplying orthogonal matrices U and V while implementing phase-truncation. Diagonal entries of the three diagonal matrices of the SVD results are abstracted and scrambling combined to construct the colormap of the ciphertext. Thus, the encrypted indexed image covers less space than the original image. For decryption, the original color image cannot be recovered without private keys which are obtained from phase-truncation and the orthogonality of V. Computer simulations are presented to evaluate the performance of the proposed algorithm. We also analyze the security of the proposed system.
NASA Astrophysics Data System (ADS)
Chen, Linfei; Gao, Xiong; Chen, Xudong; He, Bingyu; Liu, Jingyu; Li, Dan
2016-04-01
In this paper, a new optical image cryptosystem is proposed based on two-beam coherent superposition and unequal modulus decomposition. Different from the equal modulus decomposition or unit vector decomposition, the proposed method applies common vector decomposition to accomplish encryption process. In the proposed method, the original image is firstly Fourier transformed and the complex function in spectrum domain will be obtained. The complex distribution is decomposed into two vector components with unequal amplitude and phase by the common vector decomposition method. Subsequently, the two components are modulated by two random phases and transformed from spectrum domain to spatial domain, and amplitude parts are extracted as encryption results and phase parts are extracted as private keys. The advantages of the proposed cryptosystem are: four different phase and amplitude information created by the method of common vector decomposition strengthens the security of the cryptosystem, and it fully solves the silhouette problem. Simulation results are presented to show the feasibility and the security of the proposed cryptosystem.
Polymethylsilsesquioxanes through base-catalyzed redistribution of oligomethylhydridosiloxanes
RAHIMIAN,KAMYAR; ASSINK,ROGER A.; LOY,DOUGLAS A.
2000-04-04
There has been an increasing amount of interest in silsesquioxanes and polysilsesquioxanes. They have been used as models for silica surfaces and have been shown to have great potential for several industrial applications. Typical synthesis of polysilsesquioxanes involves the hydrolysis of organotricholorosilanes and/or organotrialkoxysilanes in the presence of acid or base catalysts, usually in the presence of organic solvents.
Ionic liquid supported acid/base-catalyzed production of biodiesel.
Lapis, Alexandre A M; de Oliveira, Luciane F; Neto, Brenno A D; Dupont, Jairton
2008-01-01
The transesterification (alcoholysis) reaction was successfully applied to synthesize biodiesel from vegetable oils using imidazolium-based ionic liquids under multiphase acidic and basic conditions. Under basic conditions, the combination of the ionic liquid 1-n-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (BMINTf2), alcohols, and K2CO3 (40 mol %) results in the production of biodiesel from soybean oil in high yields (>98%) and purity. H2SO4 immobilized in BMINTf2 efficiently promotes the transesterification reaction of soybean oil and various primary and secondary alcohols. In this multiphase process the acid is almost completely retained in the ionic liquid phase, while the biodiesel forms a separate phase. The recovered ionic liquid containing the acid could be reused at least six times without any significant loss in the biodiesel yield or selectivity. In both catalytic processes (acid and base), the reactions proceed as typical multiphasic systems in which the formed biodiesel accumulates as the upper phase and the glycerol by-product is selectively captured by the alcohol-ionic liquid-acid/base phase. Classical ionic liquids such as 1-n-butyl-3-methylimidazolium tetrafluoroborate and hexafluorophosphate are not stable under these acidic or basic conditions and decompose.
Multi-focus image fusion based on window empirical mode decomposition
NASA Astrophysics Data System (ADS)
Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao
2017-09-01
In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.
Nanoinformatics and DNA-based computing: catalyzing nanomedicine.
Maojo, Victor; Martin-Sanchez, Fernando; Kulikowski, Casimir; Rodriguez-Paton, Alfonso; Fritts, Martin
2010-05-01
Five decades of research and practical application of computers in biomedicine has given rise to the discipline of medical informatics, which has made many advances in genomic and translational medicine possible. Developments in nanotechnology are opening up the prospects for nanomedicine and regenerative medicine where informatics and DNA computing can become the catalysts enabling health care applications at sub-molecular or atomic scales. Although nanomedicine promises a new exciting frontier for clinical practice and biomedical research, issues involving cost-effectiveness studies, clinical trials and toxicity assays, drug delivery methods, and the implementation of new personalized therapies still remain challenging. Nanoinformatics can accelerate the introduction of nano-related research and applications into clinical practice, leading to an area that could be called "translational nanoinformatics." At the same time, DNA and RNA computing presents an entirely novel paradigm for computation. Nanoinformatics and DNA-based computing are together likely to completely change the way we model and process information in biomedicine and impact the emerging field of nanomedicine most strongly. In this article, we review work in nanoinformatics and DNA (and RNA)-based computing, including applications in nanopediatrics. We analyze their scientific foundations, current research and projects, envisioned applications and potential problems that might arise from them.
Displacement decomposition ACO based preconditioning of FEM elasticity systems
NASA Astrophysics Data System (ADS)
Sviercoski, R. F.; Margenov, S.
2013-10-01
Computational simulations of multiscale deformable porous media are routinely encountered as a part of research and development activities in a number of engineering, environmental and biomedical fields. The efficiency of multilevel iterative solution of such problems is a challenging topic on numerical methods for large-scale scientific computing, this is because predicting the mechanical behavior of such systems with hierarchical structures with multiple scales is very computationally demanding. Our main interest application concerns medium that has complex hierarchical morphology in the sense that features ranges from nanometer to millimeter scales. The goal of this work is to propose a computationally efficient numerical tool that can be used to perform everyday predictive simulations as an integral part of osteoporosis treatment, for example. To achieve that, highly heterogeneous media are considered that resembles trabecular bone tissues. The related fine-scale linear elasticity problem is of high contrast and high frequency. The finite element method (FEM) is applied for discretization of the related linear elasticity problem, using separable displacement decomposition. The new feature in this work is that at coarser levels, a block diagonal preconditioner is applied that incorporates an analytical effective tensor into the simulation, avoiding costly numerical solutions of local problems that are inherent in methods for multiscale problems. The robustness of the new proposed algorithm is measured by comparing the number of V-cycles necessary to resolve the considered multiscale problems with other well known techniques.
Sparse time-frequency decomposition based on dictionary adaptation.
Hou, Thomas Y; Shi, Zuoqiang
2016-04-13
In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions.
Spectral decomposition in multichannel recordings based on multivariate parametric identification.
Baselli, G; Porta, A; Rimoldi, O; Pagani, M; Cerutti, S
1997-11-01
A method of spectral decomposition in multichannel recordings is proposed, which represents the results of multivariate (MV) parametric identification in terms of classification and quantification of different oscillating mechanisms. For this purpose, a class of MV dynamic adjustment (MDA) models in which a MV autoregressive (MAR) network of causal interactions is fed by uncorrelated autoregressive (AR) processes is defined. Poles relevant to the MAR network closed-loop interactions (cl-poles) and poles relevant to each AR input are disentangled and accordingly classified. The autospectrum of each channel can be divided into partial spectra each relevant to an input. Each partial spectrum is affected by the cl-poles and by the poles of the corresponding input; consequently, it is decomposed into the relevant components by means of the residual method. Therefore, different oscillating mechanisms, even at similar frequencies, are classified by different poles and quantified by the corresponding components. The structure of MDA models is quite flexible and can be adapted to various sets of available signals and a priori hypotheses about the existing interactions; a graphical layout is proposed that emphasizes the oscillation sources and the corresponding closed-loop interactions. Application examples relevant to cardiovascular variability are briefly illustrated.
Effect of a base-catalyzed dechlorination process on the genotoxicity of PCB-contaminated soil
DeMarini, D.M.; Houk, V.S.; Kornel, A.; Rogers, C.J.
1992-01-01
We evaluated the genotoxicity of dichloromethane (DCM) extracts of PCB-contaminated soil before and after the soil had been treated by a base-catalyzed dechlorination process, which involved heating a mixture of the soil, polyethylene glycol, and sodium hydroxide to 250-350 C. This dechlorination process reduced by over 99% the PCB concentration in the soil, which was initially 2,200 ppm. The DCM extracts of both control and treated soils were not mutagenic in strain TA100 of Salmonella, but they were mutagenic in strain TA98. The base-catalyzed dechlorination process reduced the mutagenic potency of the soil by approximately one-half. The DCM extracts of the soils before and after treatment were equally genotoxic in a prophage-induction assay in E. coli, which detects some chlorinated organic carcinogens that were not detected by the Salmonella mutagenicity assay. These results show that treatment of PCB-contaminated soil by this base-catalyzed dechlorination process did not increase the genotoxicity of the soil.
Enzyme-based resource allocated decomposition and landscape heterogeneity in the Florida Everglades.
Penton, C Ryan; Newman, Susan
2008-01-01
Enzyme catalyzed reactions are generally considered the rate-limiting step in organic matter degradation and may be significantly influenced by the structure and composition of plant communities. Changes in these rates have the potential to effect long-term peat accumulation and influence the topography of a wetland ecosystem. To determine habitat influences on enzyme activities, we examined slough and sawgrass plots within enriched and reference phosphorus (P) sites in the Everglades. Assays were performed for the enzymes involved in carbon (C), nitrogen (N), and P cycling and lignin depolymerization. Enzyme activities were normalized and analyzed in terms of a resource allocation strategy. Plant composition was found to significantly alter the allocation of enzymatic resources due to varying substrate complexities. Potential decomposition in the slough was less influenced by lignin than in the sawgrass habitats. Additionally, an index relating hydrolytic and oxidative enzymes was significantly greater in the slough habitats, whereas C/N ratios were significantly lower. These indices suggest more favorable decomposition conditions and thus slower peat accretion within the slough communities, which may contribute to the development of elevation differences within the sawgrass ridge and slough topography of the Everglades.
Implementation of QR-decomposition based on CORDIC for unitary MUSIC algorithm
NASA Astrophysics Data System (ADS)
Lounici, Merwan; Luan, Xiaoming; Saadi, Wahab
2013-07-01
The DOA (Direction Of Arrival) estimation with subspace methods such as MUSIC (MUltiple SIgnal Classification) and ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) is based on an accurate estimation of the eigenvalues and eigenvectors of covariance matrix. QR decomposition is implemented with the Coordinate Rotation DIgital Computer (CORDIC) algorithm. QRD requires only additions and shifts [6], so it is faster and more regular than other methods. In this article the hardware architecture of an EVD (Eigen Value Decomposition) processor based on TSA (triangular systolic array) for QR decomposition is proposed. Using Xilinx System Generator (XSG), the design is implemented and the estimated logic device resource values are presented for different matrix sizes.
Decomposition method of complex optimization model based on global sensitivity analysis
NASA Astrophysics Data System (ADS)
Qiu, Qingying; Li, Bing; Feng, Peien; Gao, Yu
2014-07-01
The current research of the decomposition methods of complex optimization model is mostly based on the principle of disciplines, problems or components. However, numerous coupling variables will appear among the sub-models decomposed, thereby make the efficiency of decomposed optimization low and the effect poor. Though some collaborative optimization methods are proposed to process the coupling variables, there lacks the original strategy planning to reduce the coupling degree among the decomposed sub-models when we start decomposing a complex optimization model. Therefore, this paper proposes a decomposition method based on the global sensitivity information. In this method, the complex optimization model is decomposed based on the principle of minimizing the sensitivity sum between the design functions and design variables among different sub-models. The design functions and design variables, which are sensitive to each other, will be assigned to the same sub-models as much as possible to reduce the impacts to other sub-models caused by the changing of coupling variables in one sub-model. Two different collaborative optimization models of a gear reducer are built up separately in the multidisciplinary design optimization software iSIGHT, the optimized results turned out that the decomposition method proposed in this paper has less analysis times and increases the computational efficiency by 29.6%. This new decomposition method is also successfully applied in the complex optimization problem of hydraulic excavator working devices, which shows the proposed research can reduce the mutual coupling degree between sub-models. This research proposes a decomposition method based on the global sensitivity information, which makes the linkages least among sub-models after decomposition, and provides reference for decomposing complex optimization models and has practical engineering significance.
Batakliev, Todor; Georgiev, Vladimir; Anachkov, Metody; Rakovsky, Slavcho
2014-01-01
Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers). Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates. PMID:26109880
Batakliev, Todor; Georgiev, Vladimir; Anachkov, Metody; Rakovsky, Slavcho; Zaikov, Gennadi E
2014-06-01
Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers). Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates.
Samet, Alexander V.; Niyazymbetov, Murat E.; Semenov, Victor V.; Laikhter, Andrei L.; Evans, Dennis H.
1996-12-13
Regioselective Michael addition of nitro and heterocyclic compounds to levoglucosenone, 1, is effectively catalyzed by amines and also by cathodic electrolysis. In comparison to the base-catalyzed reaction, it was found that under electrochemical conditions the reaction proceeds under milder conditions and with higher yields. Cathodically-initiated Michael addition of thiols to levoglucosenone using small currents produces the previously unknown threo addition product in several instances. The normal erythro isomer, identified as the kinetic product, tends to be formed when large currents are used. In contrast, slow, low current electrolyses promote equilibration of the two forms so that erythro can be converted to threo by the retro reaction and readdition. Addition of 2-naphthalenethiol to (R)-(+)-apoverbenone is also reported.
NASA Astrophysics Data System (ADS)
Naya, Tomoki; Kohga, Makoto
2015-04-01
Ammonium nitrate (AN) has attracted much attention due to its clean burning nature as an oxidizer. However, an AN-based composite propellant has the disadvantages of low burning rate and poor ignitability. In this study, we added nitramine of cyclotrimethylene trinitramine (RDX) or cyclotetramethylene tetranitramine (HMX) as a high-energy material to AN propellants to overcome these disadvantages. The thermal decomposition and burning rate characteristics of the prepared propellants were examined as the ratio of AN and nitramine was varied. In the thermal decomposition process, AN/RDX propellants showed unique mass loss peaks in the lower temperature range that were not observed for AN or RDX propellants alone. AN and RDX decomposed continuously as an almost single oxidizer in the AN/RDX propellant. In contrast, AN/HMX propellants exhibited thermal decomposition characteristics similar to those of AN and HMX, which decomposed almost separately in the thermal decomposition of the AN/HMX propellant. The ignitability was improved and the burning rate increased by the addition of nitramine for both AN/RDX and AN/HMX propellants. The increased burning rates of AN/RDX propellants were greater than those of AN/HMX. The difference in the thermal decomposition and burning characteristics was caused by the interaction between AN and RDX.
Enhanced spacer-is-dielectric (sid) decomposition flow with model-based verification
NASA Astrophysics Data System (ADS)
Du, Yuelin; Song, Hua; Shiely, James; Wong, Martin D. F.
2013-03-01
Self-aligned double patterning (SADP) lithography is a leading candidate for 14nm node lower-metal layer fabrication. Besides the intrinsic overlay-tolerance capability, the accurate spacer width and uniformity control enables such technology to fabricate very narrow and dense patterns. Spacer-is-dielectric (SID) is the most popular flavor of SADP with higher flexibility in design. In the SID process, due to uniform spacer deposition, the spacer shape gets rounded at convex mandrel corners, and disregarding the corner rounding issue during SID decomposition may result in severe residue artifacts on device patterns. Previously, SADP decomposition was merely verified by Boolean operations on the decomposed layers, where the residue artifacts are not even identifiable. This paper proposes a model-based verification method for SID decomposition to identify the artifacts caused by spacer corner rounding. Then targeting residue artifact removal, an enhanced SID decomposition flow is introduced. Simulation results show that residue artifacts are removed effectively through the enhanced SID decomposition strategy.
Niang, Oumar; Thioune, Abdoulaye; El Gueirea, Mouhamed Cheikh; Deléchelle, Eric; Lemoine, Jacques
2012-09-01
The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called "sifting process" used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis.
Logic synthesis strategy based on BDD decomposition and PAL-oriented optimization
NASA Astrophysics Data System (ADS)
Opara, Adam; Kania, Dariusz
2015-12-01
A new strategy of logic synthesis for PAL-based CPLDs is presented in the paper. This approach consists of an original method of two-stage BDD-based decomposition and a two-level PAL-oriented optimization. The aim of the proposed approach is oriented towards balanced (speed/area) optimization. The first element of the strategy is original PAL-oriented decomposition. This decomposition consists in the sequential search for an input partition providing the feasibility for implementation of the free block in one PAL-based logic block containing a predefined number of product terms. The presented non-standard decomposition provides a means to minimize the area of the implemented circuit and to reduce of the necessary logic blocks in the programmable structure. The second element of the proposed logic synthesis strategy is oriented towards speed optimization. This optimization is based on utilizing tri-state buffers. Results of experiments prove that the presented synthesis strategy is especially effective for CPLD structures, which consist of PAL-based logic blocks containing a low number of product terms.
ECG baseline wander correction based on mean-median filter and empirical mode decomposition.
Xin, Yi; Chen, Yu; Hao, Wei Tuo
2014-01-01
A novel approach of ECG baseline wander correction based on mean-median filter and empirical mode decomposition is presented in this paper. The low frequency parts of the original signals were removed by the mean median filter in a nonlinear way to obtain the baseline wander estimation, then its series of IMFs were sifted by t-test after empirical mode decomposition. The proposed method, tested by the ECG signals in MIT-BIH Arrhythmia database and European ST_T database, is more effective compared with other baseline wander removal methods.
NASA Astrophysics Data System (ADS)
Ke, Xianhua; Jiang, Hao; Lv, Wen; Liu, Shiyuan
2016-03-01
Triple patterning (TP) lithography becomes a feasible technology for manufacturing as the feature size further scale down to sub 14/10 nm. In TP, a layout is decomposed into three masks followed with exposures and etches/freezing processes respectively. Previous works mostly focus on layout decomposition with minimal conflicts and stitches simultaneously. However, since any existence of native conflict will result in layout re-design/modification and reperforming the time-consuming decomposition, the effective method that can be aware of native conflicts (NCs) in layout is desirable. In this paper, a bin-based library matching method is proposed for NCs detection and layout decomposition. First, a layout is divided into bins and the corresponding conflict graph in each bin is constructed. Then, we match the conflict graph in a prebuilt colored library, and as a result the NCs can be located and highlighted quickly.
Bandyopadhyay, Biman; Kumar, Pradeep; Biswas, Partha
2017-04-27
Electronic structure calculations have been performed to investigate the role of ammonia in catalyzing the formation of sulfuric acid through hydrolysis of SO3 in Earth's atmosphere. The uncatalyzed process involves a high activation barrier and, until date, is mainly known to occur in Earth's atmosphere only when catalyzed by water and acids. Here we show that hydrolysis of SO3 can be very efficiently catalyzed by ammonia, the most abundant basic component in Earth's atmosphere. It was found, based on magnitude of relative potential energies as well as rate coefficients, that ammonia is the best among all the catalysts studied until now (water and acids) and could be a considerable factor in formation of sulfuric acid in troposphere. The calculated rate coefficient (at 298 K) of ammonia catalyzed reaction has been found to be ∼10(5)-10(7) times greater than that for water catalyzed ones. It was found, based on relative rates of ammonia and water catalyzed processes, that in troposphere ammonia, together with water, could be the key factor in determining the rate of formation of sulfuric acid. In fact, ammonia could surpass water in catalyzing sulfuric acid formation via hydrolysis of SO3 at various altitudes in troposphere depending upon their relative concentrations.
Yuan, Bing; Bernstein, Elliot R
2017-01-07
Unimolecular decomposition of energetic molecules, 3,3'-diamino-4,4'-bisfuroxan (labeled as A) and 4,4'-diamino-3,3'-bisfuroxan (labeled as B), has been explored via 226/236 nm single photon laser excitation/decomposition. These two energetic molecules, subsequent to UV excitation, create NO as an initial decomposition product at the nanosecond excitation energies (5.0-5.5 eV) with warm vibrational temperature (1170 ± 50 K for A, 1400 ± 50 K for B) and cold rotational temperature (<55 K). Initial decomposition mechanisms for these two electronically excited, isolated molecules are explored at the complete active space self-consistent field (CASSCF(12,12)/6-31G(d)) level with and without MP2 correction. Potential energy surface calculations illustrate that conical intersections play an essential role in the calculated decomposition mechanisms. Based on experimental observations and theoretical calculations, NO product is released through opening of the furoxan ring: ring opening can occur either on the S1 excited or S0 ground electronic state. The reaction path with the lowest energetic barrier is that for which the furoxan ring opens on the S1 state via the breaking of the N1-O1 bond. Subsequently, the molecule moves to the ground S0 state through related ring-opening conical intersections, and an NO product is formed on the ground state surface with little rotational excitation at the last NO dissociation step. For the ground state ring opening decomposition mechanism, the N-O bond and C-N bond break together in order to generate dissociated NO. With the MP2 correction for the CASSCF(12,12) surface, the potential energies of molecules with dissociated NO product are in the range from 2.04 to 3.14 eV, close to the theoretical result for the density functional theory (B3LYP) and MP2 methods. The CASMP2(12,12) corrected approach is essential in order to obtain a reasonable potential energy surface that corresponds to the observed decomposition behavior of these
NASA Astrophysics Data System (ADS)
Yuan, Bing; Bernstein, Elliot R.
2017-01-01
Unimolecular decomposition of energetic molecules, 3,3'-diamino-4,4'-bisfuroxan (labeled as A) and 4,4'-diamino-3,3'-bisfuroxan (labeled as B), has been explored via 226/236 nm single photon laser excitation/decomposition. These two energetic molecules, subsequent to UV excitation, create NO as an initial decomposition product at the nanosecond excitation energies (5.0-5.5 eV) with warm vibrational temperature (1170 ± 50 K for A, 1400 ± 50 K for B) and cold rotational temperature (<55 K). Initial decomposition mechanisms for these two electronically excited, isolated molecules are explored at the complete active space self-consistent field (CASSCF(12,12)/6-31G(d)) level with and without MP2 correction. Potential energy surface calculations illustrate that conical intersections play an essential role in the calculated decomposition mechanisms. Based on experimental observations and theoretical calculations, NO product is released through opening of the furoxan ring: ring opening can occur either on the S1 excited or S0 ground electronic state. The reaction path with the lowest energetic barrier is that for which the furoxan ring opens on the S1 state via the breaking of the N1—O1 bond. Subsequently, the molecule moves to the ground S0 state through related ring-opening conical intersections, and an NO product is formed on the ground state surface with little rotational excitation at the last NO dissociation step. For the ground state ring opening decomposition mechanism, the N—O bond and C—N bond break together in order to generate dissociated NO. With the MP2 correction for the CASSCF(12,12) surface, the potential energies of molecules with dissociated NO product are in the range from 2.04 to 3.14 eV, close to the theoretical result for the density functional theory (B3LYP) and MP2 methods. The CASMP2(12,12) corrected approach is essential in order to obtain a reasonable potential energy surface that corresponds to the observed decomposition behavior of
Zhao, Jing; Hu, Suisui; Zhong, Weidong; Wu, Jiguang; Shen, Zhongming; Chen, Zhong; Li, Genxi
2014-05-28
In this paper, we have proposed a new electrochemical aptasensor based on a novel ligase-assisted Exo III-catalyzed degradation reaction (LAECDR), which consists of DNA ligase-catalyzed ligation of thrombin-binding aptamer (TBA) with an extension strand (E-strand) and Exo III-catalyzed selective degradation of probe DNA, by using an improved target-induced strand displacement strategy. As a result of LAECDR, methylene blue (MB)-labeled mononucleotides can be released from the 3'-terminal of probe DNA and captured by cucurbit[7]uril-functionalized electrode to induce noticeable electrochemical response. Nevertheless, in the presence of the target protein, thrombin, the TBA that is partially complementary to probe DNA is preferentially binding with the target protein, thereby inhibiting LAECDR from taking place. The remaining intact probe DNA will prevent the terminal-attached MB from approaching to the electrode surface due to strong electrostatic repulsion, so the electrochemical response will be changed by thrombin. By tracing the electrochemical response of adsorbed MB, our aptasensor can exhibit high sensitivity for thrombin detection with a wide linear range from 100 fM to 1 nM and an extremely low detection limit of 33 fM, which can also easily distinguish thrombin in the complex serum samples with high specificity. Therefore, our aptasensor might have great potential in clinical applications in the future.
Colorimetric analysis of the decomposition of S-nitrosothiols on paper-based microfluidic devices.
Ismail, Abdulghani; Araújo, Marillya O; Chagas, Cyro L S; Griveau, Sophie; D'Orlyé, Fanny; Varenne, Anne; Bedioui, Fethi; Coltro, Wendell K T
2016-10-24
A disposable microfluidic paper-based analytical device (μPAD) was developed to easily analyse different S-nitrosothiols (RSNOs) through colorimetric measurements. RSNOs are carriers of nitric oxide (NO) that play several physiological and physiopathological roles. The quantification of RSNOs relies on their decomposition using several protocols and the colorimetric detection of the final product, NO or nitrite. μPADs were fabricated by wax printing technology in a geometry containing one central zone for the sample inlet and eight circular detection zones interconnected by microfluidic channels for decomposition and posterior detection of decayed products. Different decomposition protocols including mercuric ions and light (UV, visible, and infrared) were tested on μPADs. For this purpose, a 3D printed holder was coupled with μPADs to easily design a simultaneous decomposition procedure using different light sources. The Griess reagent was added to detect NO and nitrite produced by the different decomposition methods. μPADs were then scanned using a flat board scanner and calibration curves based on color intensity were plotted. The limit of detection (LOD) values achieved for nitrite (used as a reference compound) and S-nitrosoglutathione (GSNO) using mercuric decomposition were 3 and 4 μM, respectively. The LOD reported herein for nitrite is considered among the lowest LODs already reported for this compound using μPADs. The results also show that low-molecular-weight RSNO, namely S-nitrosocysteine, decomposes more easily than high-molecular-weight RSNOs with light. As a proof of concept, RSNOs in human plasma were successfully detected on μPADs. For this purpose, a preliminary treatment step was optimized and the presence of high-molecular-weight (HMW) RSNOs was evidenced in the available plasma samples. The concentrations of HMW-RSNOs and nitrite in the various samples ranged from 5 to 16 μM and from 37 to 58 μM, respectively.
3D tensor-based blind multispectral image decomposition for tumor demarcation
NASA Astrophysics Data System (ADS)
Kopriva, Ivica; Peršin, Antun
2010-03-01
Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).
Michelson interferometer based interleaver design using classic IIR filter decomposition.
Cheng, Chi-Hao; Tang, Shasha
2013-12-16
An elegant method to design a Michelson interferometer based interleaver using a classic infinite impulse response (IIR) filter such as Butterworth, Chebyshev, and elliptic filters as a starting point are presented. The proposed design method allows engineers to design a Michelson interferometer based interleaver from specifications seamlessly. Simulation results are presented to demonstrate the validity of the proposed design method.
2017-01-01
Biobased furanics like 5-hydroxymethylfurfural (5-HMF) are interesting platform chemicals for the synthesis of biofuel additives and polymer precursors. 5-HMF is typically prepared from C6 ketoses like fructose, psicose, sorbose and tagatose. A known byproduct is 2-hydroxyacetylfuran (2-HAF), particularly when using sorbose and psicose as the reactants. We here report an experimental and kinetic modeling study on the rate of decomposition of 2-HAF in a typical reaction medium for 5-HMF synthesis (water, Brönsted acid), with the incentive to gain insights in the stability of 2-HAF. A total of 12 experiments were performed (batch setup) in water with sulfuric acid as the catalyst (100–170 °C, CH2SO4 ranging between 0.033 and 1.37 M and an initial 2-HAF concentration between 0.04 and 0.26 M). Analysis of the reaction mixtures showed a multitude of products, of which levulinic acid (LA) and formic acid (FA) were the most prominent (Ymax,FA = 24 mol %, Ymax,LA = 10 mol %) when using HCl. In contrast, both LA and FA were formed in minor amounts when using H2SO4 as the catalyst. The decomposition reaction of 2-HAF using sulfuric acid was successfully modeled (R2 = 0.9957) using a first-order approach in 2-HAF and acid. The activation energy was found to be 98.7 (±2.2) kJ mol–1. PMID:28480150
Performance of tensor decomposition-based modal identification under nonstationary vibration
NASA Astrophysics Data System (ADS)
Friesen, P.; Sadhu, A.
2017-03-01
Health monitoring of civil engineering structures is of paramount importance when they are subjected to natural hazards or extreme climatic events like earthquake, strong wind gusts or man-made excitations. Most of the traditional modal identification methods are reliant on stationarity assumption of the vibration response and posed difficulty while analyzing nonstationary vibration (e.g. earthquake or human-induced vibration). Recently tensor decomposition based methods are emerged as powerful and yet generic blind (i.e. without requiring a knowledge of input characteristics) signal decomposition tool for structural modal identification. In this paper, a tensor decomposition based system identification method is further explored to estimate modal parameters using nonstationary vibration generated due to either earthquake or pedestrian induced excitation in a structure. The effects of lag parameters and sensor densities on tensor decomposition are studied with respect to the extent of nonstationarity of the responses characterized by the stationary duration and peak ground acceleration of the earthquake. A suite of more than 1400 earthquakes is used to investigate the performance of the proposed method under a wide variety of ground motions utilizing both complete and partial measurements of a high-rise building model. Apart from the earthquake, human-induced nonstationary vibration of a real-life pedestrian bridge is also used to verify the accuracy of the proposed method.
Grid-based electronic structure calculations: The tensor decomposition approach
NASA Astrophysics Data System (ADS)
Rakhuba, M. V.; Oseledets, I. V.
2016-05-01
We present a fully grid-based approach for solving Hartree-Fock and all-electron Kohn-Sham equations based on low-rank approximation of three-dimensional electron orbitals. Due to the low-rank structure the total complexity of the algorithm depends linearly with respect to the one-dimensional grid size. Linear complexity allows for the usage of fine grids, e.g. 81923 and, thus, cheap extrapolation procedure. We test the proposed approach on closed-shell atoms up to the argon, several molecules and clusters of hydrogen atoms. All tests show systematical convergence with the required accuracy.
Grid-based electronic structure calculations: The tensor decomposition approach
Rakhuba, M.V.; Oseledets, I.V.
2016-05-01
We present a fully grid-based approach for solving Hartree–Fock and all-electron Kohn–Sham equations based on low-rank approximation of three-dimensional electron orbitals. Due to the low-rank structure the total complexity of the algorithm depends linearly with respect to the one-dimensional grid size. Linear complexity allows for the usage of fine grids, e.g. 8192{sup 3} and, thus, cheap extrapolation procedure. We test the proposed approach on closed-shell atoms up to the argon, several molecules and clusters of hydrogen atoms. All tests show systematical convergence with the required accuracy.
Decomposition of free chlorine with tertiary ammonium.
Katano, Hajime; Uematsu, Kohei; Tatsumi, Hirosuke; Tsukatani, Toshihide
2010-01-01
The reaction of free chlorine with tertiary ammonium or amine compounds in aqueous solution was studied by the amperometry at a rotating Pt-disk electrode. The amperometric method can be applied to follow the concentration of free chlorine (c(Cl)) even in the presence of chloramine species. By addition of mono- and dibutylammonium to the solution containing free chlorine, the step-like decrease in c(Cl) was observed, indicating the rapid formation of the stable chloramine species. By addition of tributylammonium, the c(Cl) was decreased exponentially to nearly zero even if the free chlorine was present initially in excess. The c(Cl)-t curves can be explained by tributylammonium-species-catalyzed decomposition of free chlorine to chloride ion. The catalytic decomposition was observed also with the tertiary-ammonium-based anion-exchange resins. Furthermore, the anion-exchange resins exhibited the decomposition of not only free chlorine but also chloramines in water.
Catalyzed Ceramic Burner Material
Barnes, Amy S., Dr.
2012-06-29
period in accomplishing these objectives. Our work in the area of Pd-based, methane oxidation catalysts has led to the development of highly active catalysts with relatively low loadings of Pd metal using proprietary coating methods. The thermal stability of these Pd-based catalysts were characterized using SEM and BET analyses, further demonstrating that certain catalyst supports offer enhanced stability toward both PdO decomposition and/or thermal sintering/growth of Pd particles. When applied to commercially available fiber mesh substrates (both metallic and ceramic) and tested in an open-air burner, these catalyst-support chemistries showed modest improvements in the NOx emissions and radiant output compared to uncatalyzed substrates. More significant, though, was the performance of the catalyst-support chemistries on novel media substrates. These substrates were developed to overcome the limitations that are present with commercially available substrate designs and increase the gas-catalyst contact time. When catalyzed, these substrates demonstrated a 65-75% reduction in NOx emissions across the firing range when tested in an open air burner. In testing in a residential boiler, this translated into NOx emissions of <15 ppm over the 15-150 kBtu/hr firing range.
Palladium-Catalyzed Aerobic Acetoxylation of Benzene using NOx-Based Redox Mediators‡
Zultanski, Susan L.; Stahl, Shannon S.
2015-01-01
Palladium-catalyzed methods for C–H oxygenation with O2 as the stoichiometric oxidant are limited. Here, we describe the use of nitrite and nitrate sources as NOx-based redox mediators in the acetoxylation of benzene. The conditions completely avoid formation of biphenyl as a side product, and strongly favor formation of phenyl acetate over nitrobenzene (PhOAc:PhNO2 ratios up to 40:1). Under the optimized reaction conditions, with 0.1 mol% Pd(OAc)2, 136 turnovers of Pd are achieved with only 1 atm of O2 pressure. PMID:25843978
Diallo, Aboubacar; Zhao, Yu-Long; Wang, He; Li, Sha-Sha; Ren, Chuan-Qing; Liu, Qun
2012-11-16
An efficient synthesis of substituted benzenes via a base-catalyzed [3 + 3] aerobic oxidative aromatization of α,β-unsaturated carbonyl compounds with dimethyl glutaconate was reported. All the reactions were carried out under mild, metal-free conditions to afford the products in high to excellent yields with molecular oxygen as the sole oxidant and water as the sole byproduct. Furthermore, a more convenient tandem [3 + 2 + 1] aerobic oxidative aromatization reaction was developed through the in situ generation of the α,β-unsaturated carbonyl compounds from aldehydes and ketones.
Ye, Xuan; Plessow, Philipp N; Brinks, Marion K; Schelwies, Mathias; Schaub, Thomas; Rominger, Frank; Paciello, Rocco; Limbach, Michael; Hofmann, Peter
2014-04-23
The mechanistic course of the amination of alcohols with ammonia catalyzed by a structurally modified congener of Milstein's well-defined acridine-based PNP-pincer Ru complex has been investigated both experimentally and by DFT calculations. Several key Ru intermediates have been isolated and characterized. The detailed analysis of a series of possible catalytic pathways (e.g., with and without metal-ligand cooperation, inner- and outer-sphere mechanisms) leads us to conclude that the most favorable pathway for this catalyst does not require metal-ligand cooperation.
He, Jie; Yang, Xiaofang; Men, Bin; Wang, Dongsheng
2016-01-01
The heterogeneous Fenton reaction can generate highly reactive hydroxyl radicals (OH) from reactions between recyclable solid catalysts and H2O2 at acidic or even circumneutral pH. Hence, it can effectively oxidize refractory organics in water or soils and has become a promising environmentally friendly treatment technology. Due to the complex reaction system, the mechanism behind heterogeneous Fenton reactions remains unresolved but fascinating, and is crucial for understanding Fenton chemistry and the development and application of efficient heterogeneous Fenton technologies. Iron-based materials usually possess high catalytic activity, low cost, negligible toxicity and easy recovery, and are a superior type of heterogeneous Fenton catalysts. Therefore, this article reviews the fundamental but important interfacial mechanisms of heterogeneous Fenton reactions catalyzed by iron-based materials. OH, hydroperoxyl radicals/superoxide anions (HO2/O2(-)) and high-valent iron are the three main types of reactive oxygen species (ROS), with different oxidation reactivity and selectivity. Based on the mechanisms of ROS generation, the interfacial mechanisms of heterogeneous Fenton systems can be classified as the homogeneous Fenton mechanism induced by surface-leached iron, the heterogeneous catalysis mechanism, and the heterogeneous reaction-induced homogeneous mechanism. Different heterogeneous Fenton systems catalyzed by characteristic iron-based materials are comprehensively reviewed. Finally, related future research directions are also suggested. Copyright © 2015. Published by Elsevier B.V.
Classification of Underwater Signals Using Wavelet-Based Decompositions
1998-06-01
proposed by Learned and Willsky [21], uses the SVD information obtained from the power mapping, the second one selects the most within-a-class...34 SPIE, Vol. 2242, pp. 792-802, Wavelet Applications, 1994 [14] R. Coifman and D. Donoho, "Translation-Invariant Denoising ," Internal Report...J. Barsanti, Jr., Denoising of Ocean Acoustic Signals Using Wavelet-Based Techniques, MSEE Thesis, Naval Postgraduate School, Monterey, California
Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition
Lei, Yaguo; Li, Naipeng; Lin, Jing; Wang, Sizhe
2013-01-01
The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of rotating machinery. But it has the shortcoming of mode mixing in decomposing signals. To overcome this shortcoming, ensemble empirical mode decomposition (EEMD) was proposed accordingly. EEMD is able to reduce the mode mixing to some extent. The performance of EEMD, however, depends on the parameters adopted in the EEMD algorithms. In most of the studies on EEMD, the parameters were selected artificially and subjectively. To solve the problem, a new adaptive ensemble empirical mode decomposition method is proposed in this paper. In the method, the sifting number is adaptively selected, and the amplitude of the added noise changes with the signal frequency components during the decomposition process. The simulation, the experimental and the application results demonstrate that the adaptive EEMD provides the improved results compared with the original EEMD in diagnosing rotating machinery. PMID:24351666
Fault diagnosis of rotating machinery based on an adaptive ensemble empirical mode decomposition.
Lei, Yaguo; Li, Naipeng; Lin, Jing; Wang, Sizhe
2013-12-09
The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of rotating machinery. But it has the shortcoming of mode mixing in decomposing signals. To overcome this shortcoming, ensemble empirical mode decomposition (EEMD) was proposed accordingly. EEMD is able to reduce the mode mixing to some extent. The performance of EEMD, however, depends on the parameters adopted in the EEMD algorithms. In most of the studies on EEMD, the parameters were selected artificially and subjectively. To solve the problem, a new adaptive ensemble empirical mode decomposition method is proposed in this paper. In the method, the sifting number is adaptively selected, and the amplitude of the added noise changes with the signal frequency components during the decomposition process. The simulation, the experimental and the application results demonstrate that the adaptive EEMD provides the improved results compared with the original EEMD in diagnosing rotating machinery.
Decomposition-based recovery of absorbers in turbid media
Campbell, S. D.; Goodin, I. L.; Grobe, S. D.; Su, Q.; Grobe, R.
2007-12-15
We suggest that the concept of the point-spread function traditionally used to predict the blurred image pattern of various light sources embedded inside turbid media can be generalized under certain conditions to predict also the presence and location of spatially localized absorbing inhomogeneities based on shadow point-spread functions associated with each localized absorber in the medium. The combined image obtained from several absorbers can then be decomposed approximately into the arithmetic sums of these individual shadow point-spread functions with suitable weights that can be obtained from multiple-regression analysis. This technique permits the reconstruction of the location of absorbers.
Decomposition-based recovery of absorbers in turbid media
NASA Astrophysics Data System (ADS)
Campbell, S. D.; Goodin, I. L.; Grobe, S. D.; Su, Q.; Grobe, R.
2007-12-01
We suggest that the concept of the point-spread function traditionally used to predict the blurred image pattern of various light sources embedded inside turbid media can be generalized under certain conditions to predict also the presence and location of spatially localized absorbing inhomogeneities based on shadow point-spread functions associated with each localized absorber in the medium. The combined image obtained from several absorbers can then be decomposed approximately into the arithmetic sums of these individual shadow point-spread functions with suitable weights that can be obtained from multiple-regression analysis. This technique permits the reconstruction of the location of absorbers.
Decomposition based recovery of absorbers in turbid media
NASA Astrophysics Data System (ADS)
Goodin, Isaac; Rogers, Ben; Su, Q.; Grobe, R.
2009-11-01
We suggest that the concept of the point-spread function traditionally used to predict the blurred image pattern of various light sources embedded inside turbid media can be generalized under certain conditions to predict also the presence and location of spatially localized absorbing inhomogeneities based on shadow point spread functions associated with each localized absorber in the medium. The combined image obtained from several absorbers can then be decomposed approximately into the arithmetic sums of these individual shadow point spread functions with suitable weights that can be obtained from multiple regression analysis. This technique permits the reconstruction of the location of absorbers.
NASA Astrophysics Data System (ADS)
Hua, Wei; Qi, Ji; Jia, Meng
2017-05-01
Switched reluctance machines (SRMs) have attracted extensive attentions due to the inherent advantages, including simple and robust structure, low cost, excellent fault-tolerance and wide speed range, etc. However, one of the bottlenecks limiting the SRMs for further applications is its unfavorable torque ripple, and consequently noise and vibration due to the unique doubly-salient structure and pulse-current-based power supply method. In this paper, an inductance Fourier decomposition-based current-hysteresis-control (IFD-CHC) strategy is proposed to reduce torque ripple of SRMs. After obtaining a nonlinear inductance-current-position model based Fourier decomposition, reference currents can be calculated by reference torque and the derived inductance model. Both the simulations and experimental results confirm the effectiveness of the proposed strategy.
Pressing the sparsity advantage via data-based decomposition
NASA Astrophysics Data System (ADS)
Riasati, Vahid R.; Andress, Laura; Grishin, Denis
2015-05-01
Numerous ℓ1-norm reconstruction techniques have enabled exact data reconstruction with high probability from `k-sparse' data. In this work, we utilize the adaptive Gram-Schmidt technique to test the limits of compressed sensing (CS) based reconstruction using total variation. The Projection-Slice Synthetic Discriminant Function (PSDF) filter naturally lends itself to compressive sensing techniques due to the inherent dimensionality reductions of the filter generated by the projection-slice theorem, or PST. In this brief study we utilize CS for the PSDF by constructing the PSDF impulse response while iteratively reducing the AGS error terms. The truncation prioritizes the vectors with regard to the error energy levels associated with the representation of the data in the Gram- Schmidt process.
Progress of Chiral Schiff Bases with C1 Symmetry in Metal-Catalyzed Asymmetric Reactions.
Hayashi, Masahiko
2016-12-01
In this Personal Account, various chiral Schiff base-metal-catalyzed enantioselective organic reactions are reported; the Schiff bases used were O,N,O- as well as N,N,P-tridentate ligands and N,N-bidentate ligands having C1 symmetry. In particular, the enantioselective addition of trimethylsilyl cyanide, dialkylzinc, and organozinc halides to aldehydes, enantioselective 1,4-addition of dialkylzinc to cyclic and acyclic enones, and asymmetric allylic oxidation are reported. Typically, ketimine-type Schiff base-metal complexes exhibited higher reactivity and enantioselectivity compared with the corresponding aldimine-type Schiff base-metal complexes. Notably, remarkable ligand acceleration was observed for all reactions. The obtained products can be used as key intermediates for optically active natural products and pharmaceuticals.
Mindfulness-based hypnosis: blending science, beliefs, and wisdoms to catalyze healing.
Alladin, Assen
2014-01-01
We live in a global village, comprised of people with diverse cultural and religious orientations. How do we integrate these different beliefs and values into our clinical practice? Mindfulness-based psychotherapy (MBP), an evidence-based psychological intervention, provides a secular template for assimilating various cultural beliefs and wisdoms in therapies. MBP represents a cross-fertilization between Western psychological practice and Eastern meditative disciplines. Guided by MBP, this article describes how intention, mindfulness, acceptance, gratitude, and the "heart" can be combined with cognitive hypnotherapy to catalyze healing of emotional disorders-particularly depression. This integrated approach is referred to as mindfulness-based cognitive hypnotherapy (MBCH) as it assimilates cognitive hypnotherapy with mindfulness strategies. MBCH represents an attempt to broaden the comprehensiveness of hypnotherapy as an integrated form of psychotherapy. Additionally, based on new understanding of the heart as a complex information center, an innovative hypnotherapeutic strategy for generating psychophysiological coherence and psychological well-being is described.
Asymmetric 1,3-Dipolar Cycloaddition Reactions Catalyzed by Heterocycle-Based Metal Complexes
NASA Astrophysics Data System (ADS)
Suga, Hiroyuki
Highly enantioselective 1,3-dipolar cycloaddition reactions of several 1,3-dipoles, such as nitrones, nitrile oxides, nitrile imines, diazoalkanes, azomethine imines and carbonyl ylides, catalyzed by heterocyclic supramolecular type of metal complexes consisting of chiral heterocyclic compounds and metal salts were described in terms of their ability of asymmetric induction and enantioface differentiation. The scope and limitations of each cycloaddition reactions were also briefly described. Of the chiral hererocycle-based ligands, chiral bisoxazoline, 2,6-bis(oxazolinyl)pyridine, and related oxazoline ligands are shown to be quite effective in obtaining high levels of asymmtric induction. The combination of the bisoxazoline ligand derived from (1S,2R)-cis-1-amino-2-indanol and metal salts was especially efficient for asymmetric cycloaddition reactions of a number of 1,3-dipoles, such as nitrones, nitrile oxide, nitrile imines, diazoacetates and azomethine imines. The metals utilized for the heterocycle-based complexes show a crucial role for degree of asymmetric induction depending upon the 1,3-dipole used. High levels of enantioselectivity were achieved in 1,3-dipolar cycloaddition reactions of unstable carbonyl ylides with benzyloxyacetaldehyde derivatives, α-keto esters, 3-(2-alkenoyl)-2-oxazolidinones, and even vinyl ethers, which were catalyzed by Pybox-lanthanoid metal complexes.
Predicting the reference evapotranspiration based on tensor decomposition
NASA Astrophysics Data System (ADS)
Misaghian, Negin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Mohammadi, Kasra
2016-09-01
Most of the available models for reference evapotranspiration (ET0) estimation are based upon only an empirical equation for ET0. Thus, one of the main issues in ET0 estimation is the appropriate integration of time information and different empirical ET0 equations to determine ET0 and boost the precision. The FAO-56 Penman-Monteith, adjusted Hargreaves, Blaney-Criddle, Priestley-Taylor, and Jensen-Haise equations were utilized in this study for estimating ET0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Three-order tensor is used to capture three-way correlations among months, years, and ET0 information. Afterward, the latent correlations among ET0 parameters were found by the multiway analysis to enhance the quality of the prediction. The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Models are compared with respect to coefficient of determination (R 2), mean absolute error (MAE), and root-mean-square error (RMSE). The proposed tensor approach has a R 2 value of greater than 0.9 for all selected ET0 methods at both selected stations, which is acceptable for the ET0 prediction. RMSE is ranged between 0.247 and 0.485 mm day-1 at Nis station and between 0.277 and 0.451 mm day-1 at Belgrade station, while MAE is between 0.140 and 0.337 mm day-1 at Nis and between 0.208 and 0.360 mm day-1 at Belgrade station. The best performances are achieved by Priestley-Taylor model at Nis station (R 2 = 0.985, MAE = 0.140 mm day-1, RMSE = 0.247 mm day-1) and FAO-56 Penman-Monteith model at Belgrade station (MAE = 0.208 mm day-1, RMSE = 0.277 mm day-1, R 2 = 0.975).
NASA Astrophysics Data System (ADS)
Nguyen van Ye, Romain; Del-Castillo-Negrete, Diego; Spong, D.; Hirshman, S.; Farge, M.
2008-11-01
A limitation of particle-based transport calculations is the noise due to limited statistical sampling. Thus, a key element for the success of these calculations is the development of efficient denoising methods. Here we discuss denoising techniques based on Proper Orthogonal Decomposition (POD) and Wavelet Decomposition (WD). The goal is the reconstruction of smooth (denoised) particle distribution functions from discrete particle data obtained from Monte Carlo simulations. In 2-D, the POD method is based on low rank truncations of the singular value decomposition of the data. For 3-D we propose the use of a generalized low rank approximation of matrices technique. The WD denoising is based on the thresholding of empirical wavelet coefficients [Donoho et al., 1996]. The methods are illustrated and tested with Monte-Carlo particle simulation data of plasma collisional relaxation including pitch angle and energy scattering. As an application we consider guiding-center transport with collisions in a magnetically confined plasma in toroidal geometry. The proposed noise reduction methods allow to achieve high levels of smoothness in the particle distribution function using significantly less particles in the computations.
Small infrared target detection based on harmonic and sparse matrix decomposition
NASA Astrophysics Data System (ADS)
Zheng, Cheng-yong; Li, Hong
2013-06-01
Background suppressing is the main technology for infrared target detection. We present a new small infrared target detection (SIRTD) method that is also based on background suppressing. First, a new matrix decomposition model, named harmonic and sparse matrix decomposition (HSMD), is put forward for decomposing an image into a harmonic and a sparse component, which are seen as a background component and a small target component, respectively. Then, an algorithm based on augmented Lagrangian alternating direction method (ALADM) for solving HSMD is described. The main computational cost of the proposed algorithm in each iteration is that of a fast Fourier transform (FFT), which makes the proposed algorithm very fast. By searching for the maximum local energy regions in the target component, the infrared targets can be easily and accurately located. Experimental results on some infrared images show that HSMD solved by ALADM is very suitable for real-time infrared image decomposing and SIRTD.
Proper orthogonal decomposition methods for noise reduction in particle-based transport calculations
NASA Astrophysics Data System (ADS)
del-Castillo-Negrete, D.; Spong, D. A.; Hirshman, S. P.
2008-09-01
Proper orthogonal decomposition techniques to reduce noise in the reconstruction of the distribution function in particle-based transport calculations are explored. For two-dimensional steady-state problems, the method is based on low rank truncations of the singular value decomposition of a coarse-grained representation of the particle distribution function. For time-dependent two-dimensional problems or three-dimensional time-independent problems, the use of a generalized low-rank approximation of matrices technique is proposed. The methods are illustrated and tested with Monte Carlo particle simulation data of plasma collisional relaxation and guiding-center transport with collisions in a magnetically confined plasma in toroidal geometry. It is observed that the proposed noise reduction methods achieve high levels of smoothness in the particle distribution function by using significantly fewer particles in the computations.
Automatic single-image-based rain streaks removal via image decomposition.
Kang, Li-Wei; Lin, Chia-Wen; Fu, Yu-Hsiang
2012-04-01
Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.
Tissue artifact removal from respiratory signals based on empirical mode decomposition.
Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty
2013-05-01
On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal.
Tissue Artifact Removal from Respiratory Signals Based on Empirical Mode Decomposition
Liu, Shaopeng; Gao, Robert X.; John, Dinesh; Staudenmayer, John; Freedson, Patty
2013-01-01
On-line measurement of respiration plays an important role in monitoring human physical activities. Such measurement commonly employs sensing belts secured around the rib cage and abdomen of the test object. Affected by the movement of body tissues, respiratory signals typically have a low signal-to-noise ratio. Removing tissue artifacts therefore is critical to ensuring effective respiration analysis. This paper presents a signal decomposition technique for tissue artifact removal from respiratory signals, based on the empirical mode decomposition (EMD). An algorithm based on the mutual information and power criteria was devised to automatically select appropriate intrinsic mode functions (IMFs) for tissue artifact removal and respiratory signal reconstruction. Performance of the EMD-algorithm was evaluated through simulations and real-life experiments (N = 105). Comparison with low-pass filtering that has been conventionally applied confirmed the effectiveness of the technique in tissue artifacts removal. PMID:23325303
Self-adaptive image denoising based on bidimensional empirical mode decomposition (BEMD).
Guo, Song; Luan, Fangjun; Song, Xiaoyu; Li, Changyou
2014-01-01
To better analyze images with the Gaussian white noise, it is necessary to remove the noise before image processing. In this paper, we propose a self-adaptive image denoising method based on bidimensional empirical mode decomposition (BEMD). Firstly, normal probability plot confirms that 2D-IMF of Gaussian white noise images decomposed by BEMD follow the normal distribution. Secondly, energy estimation equation of the ith 2D-IMF (i=2,3,4,......) is proposed referencing that of ith IMF (i=2,3,4,......) obtained by empirical mode decomposition (EMD). Thirdly, the self-adaptive threshold of each 2D-IMF is calculated. Eventually, the algorithm of the self-adaptive image denoising method based on BEMD is described. From the practical perspective, this is applied for denoising of the magnetic resonance images (MRI) of the brain. And the results show it has a better denoising performance compared with other methods.
Frequency hopping signal detection based on wavelet decomposition and Hilbert-Huang transform
NASA Astrophysics Data System (ADS)
Zheng, Yang; Chen, Xihao; Zhu, Rui
2017-07-01
Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert-Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert-Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.
MEG masked priming evidence for form-based decomposition of irregular verbs
Fruchter, Joseph; Stockall, Linnaea; Marantz, Alec
2013-01-01
To what extent does morphological structure play a role in early processing of visually presented English past tense verbs? Previous masked priming studies have demonstrated effects of obligatory form-based decomposition for genuinely affixed words (teacher-TEACH) and pseudo-affixed words (corner-CORN), but not for orthographic controls (brothel-BROTH). Additionally, MEG single word reading studies have demonstrated that the transition probability from stem to affix (in genuinely affixed words) modulates an early evoked response known as the M170; parallel findings have been shown for the transition probability from stem to pseudo-affix (in pseudo-affixed words). Here, utilizing the M170 as a neural index of visual form-based morphological decomposition, we ask whether the M170 demonstrates masked morphological priming effects for irregular past tense verbs (following a previous study which obtained behavioral masked priming effects for irregulars). Dual mechanism theories of the English past tense predict a rule-based decomposition for regulars but not for irregulars, while certain single mechanism theories predict rule-based decomposition even for irregulars. MEG data was recorded for 16 subjects performing a visual masked priming lexical decision task. Using a functional region of interest (fROI) defined on the basis of repetition priming and regular morphological priming effects within the left fusiform and inferior temporal regions, we found that activity in this fROI was modulated by the masked priming manipulation for irregular verbs, during the time window of the M170. We also found effects of the scores generated by the learning model of Albright and Hayes (2003) on the degree of priming for irregular verbs. The results favor a single mechanism account of the English past tense, in which even irregulars are decomposed into stems and affixes prior to lexical access, as opposed to a dual mechanism model, in which irregulars are recognized as whole forms
Creating an Ethnodrama to Catalyze Dialogue in Home-Based Dementia Care.
Speechley, Mark; DeForge, Ryan T; Ward-Griffin, Catherine; Marlatt, Nicole M; Gutmanis, Iris
2015-11-01
This article describes the development of a theater script derived from a critical ethnographic study that followed people living with dementia--and their family and professional caregivers--over an 18-month period. Analysis of the ethnographic data yielded four themes that characterized home-based dementia care relationships: managing care resources, making care decisions, evaluating care practices, and reifying care norms. The research team expanded to include a colleague with playwright experience, who used these themes to write a script. A theater director was included to cast and direct the play, and finally, a videography company filmed the actors on a realistic set. To contribute to the qualitative health research and the research-based theater knowledge translation literatures, this article describes and explains the creative decisions taken as part of our effort to disseminate research focused on home-based dementia care in a way that catalyzes and fosters critical (actionable) dialogue.
Devi, B Pushpa; Singh, Kh Manglem; Roy, Sudipta
2016-01-01
This paper proposes a new watermarking algorithm based on the shuffled singular value decomposition and the visual cryptography for copyright protection of digital images. It generates the ownership and identification shares of the image based on visual cryptography. It decomposes the image into low and high frequency sub-bands. The low frequency sub-band is further divided into blocks of same size after shuffling it and then the singular value decomposition is applied to each randomly selected block. Shares are generated by comparing one of the elements in the first column of the left orthogonal matrix with its corresponding element in the right orthogonal matrix of the singular value decomposition of the block of the low frequency sub-band. The experimental results show that the proposed scheme clearly verifies the copyright of the digital images, and is robust to withstand several image processing attacks. Comparison with the other related visual cryptography-based algorithms reveals that the proposed method gives better performance. The proposed method is especially resilient against the rotation attack.
Hatay, Imren; Su, Bin; Méndez, Manuel A; Corminboeuf, Clémence; Khoury, Tony; Gros, Claude P; Bourdillon, Mélanie; Meyer, Michel; Barbe, Jean-Michel; Ersoz, Mustafa; Zális, Stanislav; Samec, Zdenek; Girault, Hubert H
2010-10-06
The diprotonated form of a fluorinated free base porphyrin, namely 5-(p-aminophenyl)-10,15,20-tris(pentafluorophenyl)porphyrin (H(2)FAP), can catalyze the reduction of oxygen by a weak electron donor, namely ferrocene (Fc). At a water/1,2-dichloroethane interface, the interfacial formation of H(4)FAP(2+) is observed by UV-vis spectroscopy and ion-transfer voltammetry, due to the double protonation of H(2)FAP at the imino nitrogen atoms in the tetrapyrrole ring. H(4)FAP(2+) is shown to bind oxygen, and the complex in the organic phase can easily be reduced by Fc to produce hydrogen peroxide as studied by two-phase reactions with the Galvani potential difference between the two phases being controlled by the partition of a common ion. Spectrophotometric measurements performed in 1,2-dichloroethane solutions clearly evidence that reduction of oxygen by Fc catalyzed by H(4)FAP(2+) only occurs in the presence of the tetrakis(pentafluorophenyl)borate (TB(-)) counteranion in the organic phase. Finally, ab initio computations support the catalytic activation of H(4)FAP(2+) on oxygen.
CPUF - a chemical-structure-based polyurethane foam decomposition and foam response model.
Fletcher, Thomas H. (Brigham Young University, Provo, UT); Thompson, Kyle Richard; Erickson, Kenneth L.; Dowding, Kevin J.; Clayton, Daniel (Brigham Young University, Provo, UT); Chu, Tze Yao; Hobbs, Michael L.; Borek, Theodore Thaddeus III
2003-07-01
A Chemical-structure-based PolyUrethane Foam (CPUF) decomposition model has been developed to predict the fire-induced response of rigid, closed-cell polyurethane foam-filled systems. The model, developed for the B-61 and W-80 fireset foam, is based on a cascade of bondbreaking reactions that produce CO2. Percolation theory is used to dynamically quantify polymer fragment populations of the thermally degrading foam. The partition between condensed-phase polymer fragments and gas-phase polymer fragments (i.e. vapor-liquid split) was determined using a vapor-liquid equilibrium model. The CPUF decomposition model was implemented into the finite element (FE) heat conduction codes COYOTE and CALORE, which support chemical kinetics and enclosure radiation. Elements were removed from the computational domain when the calculated solid mass fractions within the individual finite element decrease below a set criterion. Element removal, referred to as ?element death,? creates a radiation enclosure (assumed to be non-participating) as well as a decomposition front, which separates the condensed-phase encapsulant from the gas-filled enclosure. All of the chemistry parameters as well as thermophysical properties for the CPUF model were obtained from small-scale laboratory experiments. The CPUF model was evaluated by comparing predictions to measurements. The validation experiments included several thermogravimetric experiments at pressures ranging from ambient pressure to 30 bars. Larger, component-scale experiments were also used to validate the foam response model. The effects of heat flux, bulk density, orientation, embedded components, confinement and pressure were measured and compared to model predictions. Uncertainties in the model results were evaluated using a mean value approach. The measured mass loss in the TGA experiments and the measured location of the decomposition front were within the 95% prediction limit determined using the CPUF model for all of the
NASA Astrophysics Data System (ADS)
Hu, Yiqun; Xie, Xinwen; Liu, Xingbin; Zhou, Nanrun
2017-07-01
A novel quantum multi-image encryption algorithm based on iteration Arnold transform with parameters and image correlation decomposition is proposed, and a quantum realization of the iteration Arnold transform with parameters is designed. The corresponding low frequency images are obtained by performing 2-D discrete wavelet transform on each image respectively, and then the corresponding low frequency images are spliced randomly to one image. The new image is scrambled by the iteration Arnold transform with parameters, and the gray-level information of the scrambled image is encoded by quantum image correlation decomposition. For the encryption algorithm, the keys are iterative times, added parameters, classical binary and orthonormal basis states. The key space, the security and the computational complexity are analyzed, and all of the analyses show that the proposed encryption algorithm could encrypt multiple images simultaneously with lower computational complexity compared with its classical counterparts.
Ye, Jianchu; Tu, Song; Sha, Yong
2010-10-01
For the two-step transesterification biodiesel production made from the sunflower oil, based on the kinetics model of the homogeneous base-catalyzed transesterification and the liquid-liquid phase equilibrium of the transesterification product, the total methanol/oil mole ratio, the total reaction time, and the split ratios of methanol and reaction time between the two reactors in the stage of the two-step reaction are determined quantitatively. In consideration of the transesterification intermediate product, both the traditional distillation separation process and the improved separation process of the two-step reaction product are investigated in detail by means of the rigorous process simulation. In comparison with the traditional distillation process, the improved separation process of the two-step reaction product has distinct advantage in the energy duty and equipment requirement due to replacement of the costly methanol-biodiesel distillation column.
Szlavik, Robert B
2016-02-01
The characterization of peripheral nerve fiber distributions, in terms of diameter or velocity, is of clinical significance because information associated with these distributions can be utilized in the differential diagnosis of peripheral neuropathies. Electro-diagnostic techniques can be applied to the investigation of peripheral neuropathies and can yield valuable diagnostic information while being minimally invasive. Nerve conduction velocity studies are single parameter tests that yield no detailed information regarding the characteristics of the population of nerve fibers that contribute to the compound-evoked potential. Decomposition of the compound-evoked potential, such that the velocity or diameter distribution of the contributing nerve fibers may be determined, is necessary if information regarding the population of contributing nerve fibers is to be ascertained from the electro-diagnostic study. In this work, a perturbation-based decomposition of compound-evoked potentials is proposed that facilitates determination of the fiber diameter distribution associated with the compound-evoked potential. The decomposition is based on representing the single fiber-evoked potential, associated with each diameter class, as being perturbed by contributions, of varying degree, from all the other diameter class single fiber-evoked potentials. The resultant estimator of the contributing nerve fiber diameter distribution is valid for relatively large separations in diameter classes. It is also useful in situations where the separation between diameter classes is small and the concomitant single fiber-evoked potentials are not orthogonal.
Dückert, Heiko; Khedkar, Vivek; Waldmann, Herbert; Kumar, Kamal
2011-04-26
Lewis base catalyzed [4+2] annulation reactions between electron-deficient chromone oxa- and azadienes and acetylene carboxylates provide tricyclic benzopyrones inspired by natural products. An asymmetric synthesis of the tricyclic benzopyrones was developed by using modified cinchona alkaloids as enantiodifferentiating Lewis base catalysts.
Low-Rank Decomposition Based Restoration of Compressed Images via Adaptive Noise Estimation.
Zhang, Xinfeng; Lin, Weisi; Xiong, Ruiqin; Liu, Xianming; Ma, Siwei; Gao, Wen
2016-07-07
Images coded at low bit rates in real-world applications usually suffer from significant compression noise, which significantly degrades the visual quality. Traditional denoising methods are not suitable for the content-dependent compression noise, which usually assume that noise is independent and with identical distribution. In this paper, we propose a unified framework of content-adaptive estimation and reduction for compression noise via low-rank decomposition of similar image patches. We first formulate the framework of compression noise reduction based upon low-rank decomposition. Compression noises are removed by soft-thresholding the singular values in singular value decomposition (SVD) of every group of similar image patches. For each group of similar patches, the thresholds are adaptively determined according to compression noise levels and singular values. We analyze the relationship of image statistical characteristics in spatial and transform domains, and estimate compression noise level for every group of similar patches from statistics in both domains jointly with quantization steps. Finally, quantization constraint is applied to estimated images to avoid over-smoothing. Extensive experimental results show that the proposed method not only improves the quality of compressed images obviously for post-processing, but are also helpful for computer vision tasks as a pre-processing method.
Moving object detection based on on-line block-robust principal component analysis decomposition
NASA Astrophysics Data System (ADS)
Yang, Biao; Cao, Jinmeng; Zou, Ling
2017-07-01
Robust principal component analysis (RPCA) decomposition is widely applied in moving object detection due to its ability in suppressing environmental noises while separating sparse foreground from low rank background. However, it may suffer from constant punishing parameters (resulting in confusion between foreground and background) and holistic processing of all input frames (leading to bad real-time performance). Improvements to these issues are studied in this paper. A block-RPCA decomposition approach was proposed to handle the confusion while separating foreground from background. Input frame was initially separated into blocks using three-frame difference. Then, punishing parameter of each block was computed by its motion saliency acquired based on selective spatio-temporal interesting points. Aiming to improve the real-time performance of the proposed method, an on-line solution to block-RPCA decomposition was utilized. Both qualitative and quantitative tests were implemented and the results indicate the superiority of our method to some state-of-the-art approaches in detection accuracy or real-time performance, or both of them.
Novel approach for predicting the joint effects based on the enzyme-catalyzed kinetics.
Zheng, Min; Yao, Zhifeng; Lin, Zhifen; Fang, Shuxia; Song, Chunlei; Liu, Ying
2016-04-15
Organisms are exposed to mixtures of multiple contaminants and it is necessary to build prediction models for the joint effects, considering the high expense and the complexity of the traditional toxicity testing and the flood occurrence of environmental chemical pollutants. In this study, a new method for predicting the joint effects was developed and corresponding prediction models were constructed based on the kinetic models of enzyme-catalyzed reactions. While, we utilized Vibrio fischeri, Escherichia coli and Bacillus subtilis as model organisms and determined the chronic toxicity of the binary mixtures of sulfonamides (SAs) and sulfonamide potentiators (SAPs) (SA+SAP), the mixtures of two kinds of sulfonamides (SA+SA) and the binary mixtures of sulfonamide potentiators (SAPs) and tetracyclines (TCs) (SAP+TC) respectively. Finally, corresponding mixture toxicity data was utilized to fit and verify the prediction models for different joint effects.
Car--Parrinello Molecular Dynamics Study of Base-Catalyzed Hydrolysis Reactions
NASA Astrophysics Data System (ADS)
Alnemrat, Sufian; Vasiliev, Igor; Wang, Haobin
2011-03-01
We apply the first principles metadynamics simulation technique implemented in the Car-Parrinello molecular dynamics package to study the base-catalyzed hydrolysis of N-methylacetamide in aqueous solution. Our calculations are carried out in the framework of density functional theory combined with the hybrid BLYP exchange-correlation functional The free energy surfaces and hydrolysis reaction pathways for N-methylacetamide are examined in the presence of a hydroxide ion, and 4, 32, and 64 water molecules. We find that at least 32 water molecules must be explicitly included in metadynamics simulations to accurately describe the mechanism of the hydrolysis reaction of N-Methylacetamide. Our theoretical estimate for the dissociation energy of N-Methylacetamide is in good agreement with the results of previous experimental and theoretical studies. Supported by LANL-NMSU MOU.
Ab Initio Molecular Metadynamics Study of the Base-Catalyzed Hydrolysis of N-Methylacetamide
NASA Astrophysics Data System (ADS)
Alnemrat, Sufian; Vasiliev, Igor; Wang, Haobin
2010-10-01
We apply the first principles metadynamics simulation technique implemented in the Car-Parrinello molecular dynamics package to study the base-catalyzed hydrolysis of N-methylacetamide in aqueous solution. Our calculations are carried out in the framework of density functional theory combined with the hybrid BLYP exchange-correlation functional The free energy surfaces and hydrolysis reaction pathways for N-methylacetamide are examined in the presence of a hydroxide ion, and 4, 16, 32, and 64 water molecules. We find that at least 32 water molecules must be explicitly included in metadynamics simulations to accurately describe the mechanism of the hydrolysis reaction of N-Methylacetamide Our theoretical estimate for the dissociation energy of N-Methylacetamide is in good agreement with the results of previous experimental and theoretical studies.
NASA Astrophysics Data System (ADS)
Cai, Jianjun; Shen, Xueju; Lin, Chao
2016-01-01
We propose a security-enhanced asymmetric optical cryptosystem based on coherent superposition and equal modulus decomposition by combining full phase encryption technique with our previous cryptosystem. In the encryption process, the original image is phase encoded rather than bonded with a RPM. In the decryption process, two phase-contrast filters (PCFs) are employed to obtain the plaintext. As a consequence, the new cryptosystem guarantees high-level security to the attack based on iterative Fourier transform and maintains the good performance of our previous cryptosystem, especially conveniences. Some numerical simulations are presented to verify the validity and the performance of the modified cryptosystem.
Generation of plaintext-independent private key based on conditional decomposition strategy
NASA Astrophysics Data System (ADS)
Lin, Chao; Shen, Xueju; Lei, Ming
2016-11-01
We propose to generate the plaintext-independent private keys in optical asymmetric cryptosystem (OACS) based on the strategy of conditional decomposition (CD). Following this strategy, an OACS is designed with the principle of superposition of two vectorial beams. The proposed cryptosystem can remove the silhouette which is discovered in the two beams interference-based cryptosystem. To relieve the difficulty of key distribution, a structured spiral phase key (SSPK) is utilized instead of the random phase key (RPK). And a comparison on the performance of two kinds of keys in both the encryption and decryption process is made to show the advantage of SSPK over RPK.
Elastic full waveform inversion based on mode decomposition: the approach and mechanism
NASA Astrophysics Data System (ADS)
Wang, T. F.; Cheng, J. B.
2017-05-01
Elastic full waveform inversion (EFWI) aims to reduce the misfit between recorded and modelled multicomponent seismic data for deducing a detailed model of elastic parameters in the subsurface. Because the explicit computation and inversion of the Hessian matrix is extremely resource intensive, a gradient-based (rather than Hessian-based) minimization is generally applied for large-scale applications. However, the multiparameter trade-off effects cause cross-talks in the computed gradients and thus severely affect the convergence and the quality of the inverted model. Recently, preconditioning the gradients based on elastic wave mode decomposition has been suggested for mitigating the parameter trade-offs in the EFWI process. In this paper, we propose a mode decomposition (MD)-based EFWI approach in which the preconditioned gradients are obtained through the cross-correlation of the forward and decomposed adjoint wavefields in the time domain. Based on the decomposed Frechét derivatives, we explain the mechanism of this approach through analyses of Hessian and resolution matrices and comparison with the Gauss-Newton gradients. Numerical examples of a simple fluid-saturated model and the Marmousi-II model demonstrate that the MD-based preconditioned conjugate-gradient approach can mitigate the trade-off between the P- and S-wave velocities and achieve fast convergence without any Hessian-involved calculations.
Hussein, L; Rubenwolf, S; von Stetten, F; Urban, G; Zengerle, R; Krueger, M; Kerzenmacher, S
2011-06-15
The redox enzyme laccase from Trametes versicolor efficiently catalyzes the oxygen reduction reaction (ORR) in mediatorless biofuel cell cathodes when adsorbed onto multi-walled carbon nanotubes (MWCNTs). In this work we demonstrate that the fabrication of MWCNTs in form of buckypaper (BP) results in an excellent electrode material for laccase-catalyzed cathodes. BPs are mechanically stable, self-entangling mats with high dispersion of MWCNTs resulting in easy to handle homogeneous layers with highly mesoporous structures and excellent electrical conductivities. All biocathodes have been electrochemically investigated in oxygen-saturated buffer at pH 5 by galvanostatic polarization and potentiodynamic linear sweep voltammetry. Both methods confirm an efficient direct interaction of laccase with BP with a high open circuit potential of 0.882 V vs. normal hydrogen electrode (NHE). The high oxygen reduction performance leads to high current densities of 422±71 μA cm(-2) at a typical cathode potential of 0.744 V vs. NHE. When the current density is normalized to the mass of the electrode material (mass activity), the BP-based film electrodes exhibit a 68-fold higher current density at 0.744 V vs. NHE than electrodes fabricated from the same MWCNTs in a non-dispersed agglomerated form as packed electrodes. This clearly shows that MWCNTs can act more efficiently as cathode when prepared in form of BP. This can be attributed to reduced diffusional mass transfer limitations and enhanced electrical conductivity. BP is thus a very promising material for the construction of mediatorless laccase cathodes for ORR in biofuel cells. In addition we demonstrated that these electrodes exhibit a high tolerance towards glucose, the most common bioanode fuel. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Huang, Yan; Wang, Zhihui
2015-12-01
With the development of FPGA, DSP Builder is widely applied to design system-level algorithms. The algorithm of CL multi-wavelet is more advanced and effective than scalar wavelets in processing signal decomposition. Thus, a system of CL multi-wavelet based on DSP Builder is designed for the first time in this paper. The system mainly contains three parts: a pre-filtering subsystem, a one-level decomposition subsystem and a two-level decomposition subsystem. It can be converted into hardware language VHDL by the Signal Complier block that can be used in Quartus II. After analyzing the energy indicator, it shows that this system outperforms Daubenchies wavelet in signal decomposition. Furthermore, it has proved to be suitable for the implementation of signal fusion based on SoPC hardware, and it will become a solid foundation in this new field.
Gao, Wen-Chao; Hu, Fei; Huo, Yu-Ming; Chang, Hong-Hong; Li, Xing; Wei, Wen-Long
2015-08-07
A general method for the synthesis of oxazolines and oxazoles was developed through I2-catalyzed C-O bond formation and dehydrogenation with the same oxidant, TBHP. By simply tuning reaction bases, either oxazolines or oxazoles were selectively produced from β-acylamino ketones.
Zhong, Cheng; Liao, Tao; Tuguldur, Odbadrakh; Shi, Xiaodong
2010-05-07
A one-pot synthesis of substituted dihydrofurans was developed through a Lewis base-catalyzed three-component cascade condensation between nitroalkenes, aldehydes, and 1,3-dicarbonyl compounds. The desired cyclization products were prepared with a large substrate scope (22 examples) and excellent diastereoselectivity (only trans isomers) in good to excellent yields (up to 95%).
Huang, Wentao; Sun, Hongjian; Wang, Weijie
2017-01-01
Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD’s theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis. PMID:28587198
Huang, Wentao; Sun, Hongjian; Wang, Weijie
2017-06-03
Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD's theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis.
Wu, Jingjing; Liu, Wei; Liu, Zhengjun; Liu, Shutian
2015-10-20
We analyze and present an attack scheme of the asymmetric optical cryptosystem proposed recently based on coherent superposition and equal modulus decomposition [Opt. Lett.40, 475 (2015)OPLEDP0146-959210.1364/OL.40.000475]. We prove that the attacker can recover the original image with the ciphertext and public keys through the amplitude-phase retrieval algorithm by using two constraints. One constraint of the amplitude-phase retrieval algorithm is the public key and the other is obtained through the analysis of the cryptosystem. The simulation results demonstrate the feasibility of the attack method.
Adaptive aggregation-based domain decomposition multigrid for twisted mass fermions
NASA Astrophysics Data System (ADS)
Alexandrou, Constantia; Bacchio, Simone; Finkenrath, Jacob; Frommer, Andreas; Kahl, Karsten; Rottmann, Matthias
2016-12-01
The adaptive aggregation-base domain decomposition multigrid method [A. Frommer et al., SIAM J. Sci. Comput. 36, A1581 (2014)] is extended for two degenerate flavors of twisted mass fermions. By fine-tuning the parameters we achieve a speed-up of the order of a hundred times compared to the conjugate gradient algorithm for the physical value of the pion mass. A thorough analysis of the aggregation parameters is presented, which provides a novel insight into multigrid methods for lattice quantum chromodynamics independently of the fermion discretization.
NASA Astrophysics Data System (ADS)
Penenko, Alexey; Antokhin, Pavel
2016-11-01
The performance of a variational data assimilation algorithm for a transport and transformation model of atmospheric chemical composition is studied numerically in the case where the emission inventories are missing while there are additional in situ indirect concentration measurements. The algorithm is based on decomposition and splitting methods with a direct solution of the data assimilation problems at the splitting stages. This design allows avoiding iterative processes and working in real-time. In numerical experiments we study the sensitivity of data assimilation to measurement data quantity and quality.
Yang, Bang-hua; Yan, Guo-zheng; Yan, Rong-guo; Wu, Ting
2006-12-01
A method based on wavelet packet best basis decomposition (WPBBD) is investigated for the purpose of extracting features of electroencephalogram signals produced during motor imagery tasks in brain-computer interfaces. The method includes the following three steps. (1) Original signals are decomposed by wavelet packet transform (WPT) and a wavelet packet library can be formed. (2) The best basis for classification is selected from the library. (3) Subband energies included in the best basis are used as effective features. Three different motor imagery tasks are discriminated using the features. The WPBBD produces a 70.3% classification accuracy, which is 4.2% higher than that of the existing wavelet packet method.
NASA Astrophysics Data System (ADS)
Ling, Zhao; Yeling, Wang; Guijun, Hu; Yunpeng, Cui; Jian, Shi; Li, Li
2013-07-01
Recursive least squares constant modulus algorithm based on QR decomposition (QR-RLS-CMA) is first proposed as the polarization demultiplexing method. We compare its performance with the stochastic gradient descent constant modulus algorithm (SGD-CMA) and the recursive least squares constant modulus algorithm (RLS-CMA) in a polarization-division-multiplexing system with coherent detection. It is demonstrated that QR-RLS-CMA is an efficient demultiplexing algorithm which can avoid the problem of step-length choice in SGD-CMA. Meanwhile, it also has better symbol error rate (SER) performance and more stable convergence property.
An ISAR imaging algorithm for the space satellite based on empirical mode decomposition theory
NASA Astrophysics Data System (ADS)
Zhao, Tao; Dong, Chun-zhu
2014-11-01
Currently, high resolution imaging of the space satellite is a popular topic in the field of radar technology. In contrast with regular targets, the satellite target often moves along with its trajectory and simultaneously its solar panel substrate changes the direction toward the sun to obtain energy. Aiming at the imaging problem, a signal separating and imaging approach based on the empirical mode decomposition (EMD) theory is proposed, and the approach can realize separating the signal of two parts in the satellite target, the main body and the solar panel substrate and imaging for the target. The simulation experimentation can demonstrate the validity of the proposed method.
Single-Facility Scheduling over Long Time Horizons by Logic-Based Benders Decomposition
NASA Astrophysics Data System (ADS)
Coban, Elvin; Hooker, John N.
Logic-based Benders decomposition can combine mixed integer programming and constraint programming to solve planning and scheduling problems much faster than either method alone. We find that a similar technique can be beneficial for solving pure scheduling problems as the problem size scales up. We solve single-facility non-preemptive scheduling problems with time windows and long time horizons that are divided into segments separated by shutdown times (such as weekends). The objective is to find feasible solutions, minimize makespan, or minimize total tardiness.
Decomposition of LiDAR waveforms by B-spline-based modeling
NASA Astrophysics Data System (ADS)
Shen, Xiang; Li, Qing-Quan; Wu, Guofeng; Zhu, Jiasong
2017-06-01
Waveform decomposition is a widely used technique for extracting echoes from full-waveform LiDAR data. Most previous studies recommended the Gaussian decomposition approach, which employs the Gaussian function in laser pulse modeling. As the Gaussian-shape assumption is not always satisfied for real LiDAR waveforms, some other probability distributions (e.g., the lognormal distribution, the generalized normal distribution, and the Burr distribution) have also been introduced by researchers to fit sharply-peaked and/or heavy-tailed pulses. However, these models cannot be universally used, because they are only suitable for processing the LiDAR waveforms in particular shapes. In this paper, we present a new waveform decomposition algorithm based on the B-spline modeling technique. LiDAR waveforms are not assumed to have a priori shapes but rather are modeled by B-splines, and the shape of a received waveform is treated as the mixture of finite transmitted pulses after translation and scaling transformation. The performance of the new model was tested using two full-waveform data sets acquired by a Riegl LMS-Q680i laser scanner and an Optech Aquarius laser bathymeter, comparing with three classical waveform decomposition approaches: the Gaussian, generalized normal, and lognormal distribution-based models. The experimental results show that the B-spline model performed the best in terms of waveform fitting accuracy, while the generalized normal model yielded the worst performance in the two test data sets. Riegl waveforms have nearly Gaussian pulse shapes and were well fitted by the Gaussian mixture model, while the B-spline-based modeling algorithm produced a slightly better result by further reducing 6.4% of fitting residuals, largely benefiting from alleviating the adverse impact of the ringing effect. The pulse shapes of Optech waveforms, on the other hand, are noticeably right-skewed. The Gaussian modeling results deviated significantly from original signals, and
Holographic wavefront sensor based on Karhunen-Loève decomposition
NASA Astrophysics Data System (ADS)
Anzuola, Esdras; Zepp, Andreas; Gladysz, Szymon; Stein, Karin
2016-09-01
In this paper we introduce the use of Karhunen-Loève functions as a basis set to decompose atmospheric phase aberrations in a digital holographic wavefront sensor (HWS). We show that the intermodal crosstalk when using Karhunen-Loève functions is reduced in comparison to the Zernike decomposition. Additionally, the sensor's response showed an improved linearity and better robustness to scintillation. Intermodal crosstalk remains a significant problem for this sensor but operation of an adaptive optics system based on HWS is less challenging when using Karhunen-Loève functions instead of Zernike polynomials.
Cure reaction of epoxy resins catalyzed by graphite-based nanofiller
NASA Astrophysics Data System (ADS)
Corcione, C. Esposito; Acocella, Maria Rosaria; Giuri, Antonella; Maffezzoli, Alfonso; Guerra, Gaetano
2015-12-01
A significant effort was directed to the synthesis of graphene stacks/epoxy nanocomposites and to the analysis of the effect of a graphene precursor on cure reaction of a model epoxy matrix. A comparative thermal analysis of epoxy resins filled with an exfoliated graphite oxide eGO were conducted. The main aim was to understand the molecular origin of the influence of eGO on the Tg of epoxy resins. The higher Tg values previously observed for low curing temperatures, for epoxy resins with graphite-based nanofillers, were easily rationalized by a catalytic activity of graphitic layers on the reaction between the epoxy and amine groups of the resin, which leads to higher crosslinking density in milder conditions. A kinetic analysis of the cure mechanism of the epoxy resin associated to the catalytical activity of the graphite based filler was performed by isothermal DSC measurements. The DSC results showed that the addition of graphite based filler greatly increased the enthalpy of epoxy reaction and the reaction rate, confirming the presence of a catalytic activity of graphitic layers on the crosslinking reaction between the epoxy resin components (epoxide oligomer and di-amine). A kinetic modelling analysis, arising from an auto-catalyzed reaction mechanism, was finally applied to isothermal DSC data, in order to predict the cure mechanism of the epoxy resin in presence of the graphite based nanofiller.
Ning, J. G.; Chu, L.; Ren, H. L.
2014-08-28
We base a quantitative acoustic emission (AE) study on fracture processes in alumina ceramics on wavelet packet decomposition and AE source location. According to the frequency characteristics, as well as energy and ringdown counts of AE, the fracture process is divided into four stages: crack closure, nucleation, development, and critical failure. Each of the AE signals is decomposed by a 2-level wavelet package decomposition into four different (from-low-to-high) frequency bands (AA{sub 2}, AD{sub 2}, DA{sub 2}, and DD{sub 2}). The energy eigenvalues P{sub 0}, P{sub 1}, P{sub 2}, and P{sub 3} corresponding to these four frequency bands are calculated. By analyzing changes in P{sub 0} and P{sub 3} in the four stages, we determine the inverse relationship between AE frequency and the crack source size during ceramic fracture. AE signals with regard to crack nucleation can be expressed when P{sub 0} is less than 5 and P{sub 3} more than 60; whereas AE signals with regard to dangerous crack propagation can be expressed when more than 92% of P{sub 0} is greater than 4, and more than 95% of P{sub 3} is less than 45. Geiger location algorithm is used to locate AE sources and cracks in the sample. The results of this location algorithm are consistent with the positions of fractures in the sample when observed under a scanning electronic microscope; thus the locations of fractures located with Geiger's method can reflect the fracture process. The stage division by location results is in a good agreement with the division based on AE frequency characteristics. We find that both wavelet package decomposition and Geiger's AE source locations are suitable for the identification of the evolutionary process of cracks in alumina ceramics.
Second test of base hydrolysate decomposition in a 0.04 gallon per minute scale reactor
Cena, R.J.; Thorsness, C.B.; Coburn, T.T.; Watkins, B.E.
1994-10-11
LLNL has built and operated a pilot plant for processing oil shale using recirculating hot solids. This pilot plant, was adapted in 1993 to demonstrate the feasibility of decomposing base hydrolysate, a mixture of sodium nitrite, sodium formate and other constituents. This material is the waste stream from the base hydrolysis process for destruction of energetic materials. In the Livermore process, the waste feed is thermally treated in a moving packed bed of ceramic spheres, where constituents in the waste decompose, in the presence of carbon dioxide, to form solid sodium carbonate and a suite of gases including: methane, carbon monoxide, oxygen, nitrogen oxides, ammonia and possibly molecular nitrogen. The ceramic spheres are circulated and heated, providing the energy required for thermal decomposition. The spheres provide a large surface area for evaporation and decomposition to occur, avoiding sticking and agglomeration of the waste. We performed a 2.5 hour test of the solids recirculation system, with continuous injection of approximately 0.04 gal/min of waste. Gasses from the packed bed reactor were directed through the lift pipe and water was not condensed. Potassium carbonate (0.356 M) was added to the hydrolysate prior to its introduction to the retort. Continuous on-line gas analysis was invaluable in tracking the progress of the experiment and quantifying the decomposition products. Analyses showed the primary solid product, collected in the lift exit cyclone, was indeed sodium carbonate, as expected. For the reactor condition studied in this test, N{sub 2}O was found to be the primary nitrogen bearing gas species. In the test, approximately equal quantities of ammonia and nitrogen bearing oxide gases were produced. Under proper conditions, this ammonia and NO{sub x} can be recombined downstream to form N{sub 2} and O{sub 2} as the primary effluent gases.
Direct decomposition of methane over SBA-15 supported Ni, Co and Fe based bimetallic catalysts
NASA Astrophysics Data System (ADS)
Pudukudy, Manoj; Yaakob, Zahira; Akmal, Zubair Shamsul
2015-03-01
Thermocatalytic decomposition of methane is an alternative route for the production of COx-free hydrogen and carbon nanomaterials. In this work, a set of novel Ni, Co and Fe based bimetallic catalysts supported over mesoporous SBA-15 was synthesized by a facile wet impregnation route, characterized for their structural, textural and reduction properties and were successfully used for the methane decomposition. The fine dispersion of metal oxide particles on the surface of SBA-15, without affecting its mesoporous texture was clearly shown in the low angle X-ray diffraction patterns and the transmission electron microscopy (TEM) images. The nitrogen sorption analysis showed the reduced specific surface area and pore volume of SBA-15, after metal loading due to the partial filling of hexagonal mesopores by metal species. The results of methane decomposition experiments indicated that all of the bimetallic catalysts were highly active and stable for the reaction at 700 °C even after 300 min of time on stream (TOS). However, a maximum hydrogen yield of ∼56% was observed for the NiCo/SBA-15 catalyst within 30 min of TOS. A high catalytic stability was shown by the CoFe/SBA-15 catalyst with 51% of hydrogen yield during the course of reaction. The catalytic stability of the bimetallic catalysts was attributed to the formation of bimetallic alloys. Moreover, the deposited carbons were found to be in the form of a new set of hollow multi-walled nanotubes with open tips, indicating a base growth mechanism, which confirm the selectivity of SBA-15 supported bimetallic catalysts for the formation of open tip carbon nanotubes. The Raman spectroscopic and thermogravimetric analysis of the deposited carbon nanotubes over the bimetallic catalysts indicated their higher graphitization degree and oxidation stability.
Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection.
Qian, Dong; Wang, Bei; Qing, Xiangyun; Zhang, Tao; Zhang, Yu; Wang, Xingyu; Nakamura, Masatoshi
2017-08-01
Daytime short nap involves physiological processes, such as alertness, drowsiness and sleep. The study of the relationship between drowsiness and nap based on physiological signals is a great way to have a better understanding of the periodical rhymes of physiological states. A model of Bayesian nonnegative CP decomposition (BNCPD) was proposed to extract common multiway features from the group-level electroencephalogram (EEG) signals. As an extension of the nonnegative CP decomposition, the BNCPD model involves prior distributions of factor matrices, while the underlying CP rank could be determined automatically based on a Bayesian nonparametric approach. In terms of computational speed, variational inference was applied to approximate the posterior distributions of unknowns. Extensive simulations on the synthetic data illustrated the capability of our model to recover the true CP rank. As a real-world application, the performance of drowsiness detection during daytime short nap by using the BNCPD-based features was compared with that of other traditional feature extraction methods. Experimental results indicated that the BNCPD model outperformed other methods for feature extraction in terms of two evaluation metrics, as well as different parameter settings. Our approach is likely to be a useful tool for automatic CP rank determination and offering a plausible multiway physiological information of individual states.
Decomposition of Imidazolium-Based Ionic Liquids in Contact with Lithium Metal.
Schmitz, Paulo; Jakelski, Rene; Pyschik, Marcelina; Jalkanen, Kirsi; Nowak, Sascha; Winter, Martin; Bieker, Peter
2017-03-09
Ionic liquids (ILs) are considered to be suitable electrolyte components for lithium-metal batteries. Imidazolium cation based ILs were previously found to be applicable for battery systems with a lithium-metal negative electrode. However, herein it is shown that, in contrast to the well-known IL N-butyl-N-methylpyrrolidinium bis[(trifluoromethyl)sulfonyl]imide ([Pyr14 ][TFSI]), 1-ethyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([C2MIm][TFSI]) and 1-butyl-3-methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ([C4MIm][TFSI]) are chemically unstable versus metallic lithium. A lithium-metal sheet was immersed in pure imidazolium-based IL samples and aged at 60 °C for 28 days. Afterwards, the aged IL samples were investigated to deduce possible decomposition products of the imidazolium cation. The chemical instability of the ILs in contact with lithium metal and a possible decomposition starting point are shown for the first time. Furthermore, the investigated imidazolium-based ILs can be utilized for lithium-metal batteries through the addition of the solid-electrolyte interphase (SEI) film-forming additive fluoroethylene carbonate. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Inverse Method of Centrifugal Pump Impeller Based on Proper Orthogonal Decomposition (POD) Method
NASA Astrophysics Data System (ADS)
Zhang, Ren-Hui; Guo, Rong; Yang, Jun-Hu; Luo, Jia-Qi
2017-07-01
To improve the accuracy and reduce the calculation cost for the inverse problem of centrifugal pump impeller, the new inverse method based on proper orthogonal decomposition (POD) is proposed. The pump blade shape is parameterized by quartic Bezier curve, and the initial snapshots is generated by introducing the perturbation of the blade shape control parameters. The internal flow field and its hydraulic performance is predicted by CFD method. The snapshots vector includes the blade shape parameter and the distribution of blade load. The POD basis for the snapshots set are deduced by proper orthogonal decomposition. The sample vector set is expressed in terms of the linear combination of the orthogonal basis. The objective blade shape corresponding to the objective distribution of blade load is obtained by least square fit. The Iterative correction algorithm for the centrifugal pump blade inverse method based on POD is proposed. The objective blade load distributions are corrected according to the difference of the CFD result and the POD result. The two dimensional and three dimensional blade calculation cases show that the proposed centrifugal pump blade inverse method based on POD have good convergence and high accuracy, and the calculation cost is greatly reduced. After two iterations, the deviation of the blade load and the pump hydraulic performance are limited within 4.0% and 6.0% individually for most of the flow rate range. This paper provides a promising inverse method for centrifugal pump impeller, which will benefit the hydraulic optimization of centrifugal pump.
Zhang, Lisha; Huang, Ru; Liu, Weipeng; Liu, Hongxing; Zhou, Xiaoming; Xing, Da
2016-12-15
Foodborne pathogens pose a significant threat to human health worldwide. The identification of foodborne pathogens needs to be rapid, accurate and convenient. Here, we constructed a nanoparticle cluster (NPC) catalyzed signal amplification biosensor for foodborne pathogens visual detection. In this work, vancomycin (Van), a glycopeptide antibiotic for Gram-positive bacteria, was used as the first molecular recognition agent to capture Listeria monocytogenes (L. monocytogenes). Fe3O4 NPC modified aptamer, was used as the signal amplification nanoprobe, specifically recognize to the cell wall of L. monocytogenes. As vancomycin and aptamer recognize L. monocytogenes at different sites, the sandwich recognition showed satisfied specificity. Compared to individual Fe3O4 nanoparticle (NP), NPC exhibit collective effect-enhanced catalytic activity for the color reaction of chromogenic substrate. The change in absorbance or color could represent the concentration of target. Using the Fe3O4 NPC-based signal amplification method, L. monocytogenes whole cells could be directly assayed within a linear range of 5.4×10(3)-10(8) cfu/mL and a visual limit of detection of 5.4×10(3) cfu/mL. Fe3O4 NPC-based method was more sensitive than the Fe3O4 NP-based method. All these attractive characteristics of highly sensitivity, visual and labor-saving, make the biosensor possess a potential application for foodborne pathogenic bacteria detection.
Dual Lewis Acid/Lewis Base Catalyzed Acylcyanation of Aldehydes: A Mechanistic Study.
Laurell Nash, Anna; Hertzberg, Robin; Wen, Ye-Qian; Dahlgren, Björn; Brinck, Tore; Moberg, Christina
2016-03-07
A mechanistic investigation, which included a Hammett correlation analysis, evaluation of the effect of variation of catalyst composition, and low-temperature NMR spectroscopy studies, of the Lewis acid-Lewis base catalyzed addition of acetyl cyanide to prochiral aldehydes provides support for a reaction route that involves Lewis base activation of the acyl cyanide with formation of a potent acylating agent and cyanide ion. The cyanide ion adds to the carbonyl group of the Lewis acid activated aldehyde. O-Acylation by the acylated Lewis base to form the final cyanohydrin ester occurs prior to decomplexation from titanium. For less reactive aldehydes, the addition of cyanide is the rate-determining step, whereas, for more reactive, electron-deficient aldehydes, cyanide addition is rapid and reversible and is followed by rate-limiting acylation. The resting state of the catalyst lies outside the catalytic cycle and is believed to be a monomeric titanium complex with two alcoholate ligands, which only slowly converts into the product.
Long, Ran; Huang, Hao; Li, Yaping; Song, Li; Xiong, Yujie
2015-11-25
Oxidation reactions by molecular oxygen (O2 ) over palladium (Pd)-based nanomaterials are a series of processes crucial to the synthesis of fine chemicals. In the past decades, investigations of related catalytic materials have mainly been focused on the synthesis of Pd-based nanomaterials from the angle of tailoring their surface structures, compositions and supporting materials, in efforts to improve their activities in organic reactions. From the perspective of rational materials design, it is imperative to address the fundamental issues associated with catalyst performance, one of which should be oxygen activation by Pd-based nanomaterials. Here, the fundamentals that account for the transformation from O2 to reactive oxygen species over Pd, with a focus on singlet O2 and its analogue, are introduced. Methods for detecting and differentiating species are also presented to facilitate future fundamental research. Key factors for tuning the oxygen activation efficiencies of catalytic materials are then outlined, and recent developments in Pd-catalyzed oxygen-related organic reactions are summarized in alignment with each key factor. To close, we discuss the challenges and opportunities for photocatalysis research at this unique intersection as well as the potential impact on other research fields.
Johnson, R.T. Jr.; Biefeld, R.M.
1981-08-01
The temperature dependence of the electrical conductivity and thermal decomposition characteristics of several phenolic- and silicone-based materials of interest for fireset case housings have been measured to 600 to 700/sup 0/C. The materials are phenolic or silicone resins reinforced with glass chopped fabric or cloth. The conductivity temperature dependence was measured during decomposition in a nitrogen atmosphere at a heating rate of approx. 10/sup 0/C/minute. Applied electric fields were from 4 x 10/sup 2/ to 4 x 10/sup 3/ volts/cm. Thermal decomposition characteristics were investigated by mass spectroscopy in vacuum and thermal gravimetric analysis in nitrogen and air. Nearly ohmic voltage-current characteristics were obtained, except where decomposition and/or outgassing was pronounced.
Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun
2017-01-01
This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank-(L1,L2,·) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method. PMID:28448431
Gao, Yu-Fei; Gui, Guan; Xie, Wei; Zou, Yan-Bin; Yang, Yue; Wan, Qun
2017-04-27
This paper investigates a two-dimensional angle of arrival (2D AOA) estimation algorithm for the electromagnetic vector sensor (EMVS) array based on Type-2 block component decomposition (BCD) tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- ( L 1 , L 2 , · ) BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD) method.
Liu, Li; Lai, Choi-Hong; Zhou, Shao-Dan; Xie, Fen; Rui, Lu
2011-04-01
In order to predict variations of drug concentration during a given period of time, numerical solutions of pharmacokinetic models need to be obtained efficiently. Analytical solutions of linear pharmacokinetic models are usually obtained using the Laplace transform and inverse Laplace tables. The derivations of solutions to complex nonlinear models are tedious, and such solution process may be difficult to implement as a robust software code. For nonlinear models, the fourth-order Runge-Kutta (RK4) is the most classical numerical method in obtaining approximate numerical solutions, which is impossible to be implemented in distributed computing environments without much modification. The reason is that numerical solutions obtained by using RK4 can only be computed in sequential time steps. In this paper, time-domain decomposition methods are adapted for nonlinear pharmacokinetic models. The numerical Inverse Laplace method for PharmacoKinetic models (ILPK) is implemented to solve pharmacokinetic models with iterative inverse Laplace transform in each time interval. The distributed ILPK algorithm, which is based on a two-level time-domain decomposition concept, is proposed to improve its efficiency. Solutions on the coarser temporal mesh at the top level are obtained one by one, and then those on the finer temporal mesh at the bottom level are calculated concurrently by using those initial solutions that have been obtained at the top level decomposition. Accuracy and efficiency of the proposed algorithm and its distributed equivalent are investigated by using several test models. Results indicate that the ILPK algorithm and its distributed equivalent are good candidates for both linear and nonlinear pharmacokinetic models.
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.
NASA Astrophysics Data System (ADS)
Chen, Yangkang
2016-07-01
The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural filtering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic profiles that have dip conflicts. In order to remove the limitation of seislet thresholding in dealing with conflicting-dip data, I propose a dip-separated filtering strategy. In this method, I first use an adaptive empirical mode decomposition based dip filter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the final denoised data. Compared with other dip filters, the empirical mode decomposition based dip filter is data-adaptive. One only needs to specify the number of dip components to be separated. Both complicated synthetic and field data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural filtering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.
[A new method of tremor diagnosis based on singular value decomposition of EMD].
Ai, Lingmei; Wang, Jue
2009-12-01
Aiming at three kinds of tremor, including essential tremor (ET), Parkinsonian disease (PD) tremor and physiological tremor (PT), which are subjected to frequent clinical misdiagnosis, a new method based on singular value decomposition (SVD) of empirical mode decomposition (EMD) and support vector machine (SVM) for the recognition of tremor is proposed in this paper. First, the hand acceleration signals of three different types of 40 tremor voluntary subjects were collected on the basis of informed consent, and the EMD method was used to decompose the signals into a number of stationary intrinsic mode functions (IMFs). Then the preceding four IMFs which could describe signals were selected, and the initial feature vector matrixes were formed. After the application of SVD technique to the initial feature vector matrixes, the singular values were obtained and used as the feature vectors of tremor types to be put in the support vector machine classifier as well as in the identification of tremor types. The results of experiment have shown that the proposed diagnosis method based on SVD of EMD and SVM can extract tremor features effectively and identify tremor types accurately. It also provides a new assistant approach for clinical diagnosis of tremor.
NASA Astrophysics Data System (ADS)
Chenhua, Shen; Yani, Yan
2017-02-01
We present a new tool for spatiotemporal pattern decomposition and utilize this new tool to decompose spatiotemporal patterns of monthly mean precipitation from January 1957 to May 2015 in Taihu Lake Basin, China. Our goal is to show that this new tool can mine more hidden information than empirical orthogonal function (EOF). First, based on EOF and empirical mode decomposition (EMD), the time series which is an average over the study region is decomposed into a variety of intrinsic mode functions (IMFs) and a residue by means of EMD. Then, these IMFs are supposed to be explanatory variables and a time series of precipitation in every station is considered as a dependent variable. Next, a linear multivariate regression equation is derived and corresponding coefficients are estimated. These estimated coefficients are physically interpreted as spatial coefficients and their physical meaning is an orthogonal projection between IMF and a precipitation time series in every station. Spatial patterns are presented depending on spatial coefficients. The spatiotemporal patterns include temporal patterns and spatial patterns at various timescales. Temporal pattern is obtained by means of EMD. Based on this temporal pattern, spatial patterns at various timescales will be gotten. The proposed tool has been applied in decomposition of spatiotemporal pattern of monthly mean precipitation in Taihu Lake Basin, China. Since spatial patterns are associated with intrinsic frequency, the new and individual spatial patterns are detected and explained physically. Our analysis shows that this new tool is reliable and applicable for geophysical data in the presence of nonstationarity and long-range correlation and can handle nonstationary spatiotemporal series and has the capacity to extract more hidden time-frequency information on spatiotemporal patterns.
Zhang, Meihe; Yuan, Ruo; Chai, Yaqin; Chen, Shihong; Zhong, Huaan; Wang, Cun; Cheng, Yinfeng
2012-02-15
A novel cholesterol biosensor was prepared based on gold nanoparticles-catalyzed luminol electrogenerated chemiluminescence (ECL). Firstly, l-cysteine-reduced graphene oxide composites were modified on the surface of a glassy carbon electrode. Then, gold nanoparticles (AuNPs) were self-assembled on it. Subsequently, cholesterol oxidase (ChOx) was adsorbed on the surface of AuNPs to construct a cholesterol biosensor. The stepwise fabrication processes were characterized with cyclic voltammetry and atomic force microscopy. The ECL behaviors of the biosensor were also investigated. It was found that AuNPs not only provided larger surface area for higher ChOx loading but also formed the nano-structured interface on the electrode surface to improve the analytical performance of the ECL biosensor for cholesterol. Besides, based on the efficient catalytic ability of AuNPs to luminol ECL, the response of the biosensor to cholesterol was linear range from 3.3 μM to 1.0 mM with a detection limit of 1.1 μM (S/N=3). In addition, the prepared ECL biosensor exhibited satisfying reproducibility, stability and selectivity. Taking into account the advantages of ECL, we confidently expect that ECL would have potential applications in biotechnology and clinical diagnosis.
[Novel access to indazoles based on palladium-catalyzed amination chemistry].
Inamoto, Kiyofumi
2008-07-01
Two efficient methods to construct the indazole nucleus have been developed, both of which utilize palladium-catalyzed intramolecular carbon-nitrogen bond formation. One is based on intramolecular Buchwald-Hartwig amination reaction of 2-halobenzophenone tosylhydrazones. The catalyst system we developed for this reaction allows the cyclization to proceed under very mild conditions and thus could be applied to a wide range of substrates with acid- or base-sensitive functional groups. Furthermore, this methodology could be applied for the construction of benzoisoxazole ring system. In addition, catalytic C-H activation with palladium followed by intramolecular amination of benzophenone tosylhydrazones was also accomplished with the aid of the catalyst system such as Pd(OAc)(2)/Cu(OAc)(2)/AgOCOCF(3), which gave another route to indazoles. Using this combination, indazoles with various functional groups could be obtained in good to high yields, especially in the case of substrates having electron donating group such as methoxy group on benzene ring. Interesting chemo- and regioselectivity were also observed in this reaction.
Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis
NASA Astrophysics Data System (ADS)
Kojima, S.; Hensley, S.
2012-12-01
There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume
FETI Prime Domain Decomposition base Parallel Iterative Solver Library Ver.1.0
2003-09-15
FETI Prime is a library for the iterative solution of linear equations in solid and structural mechanics. The algorithm employs preconditioned conjugate gradients, with a domain decomposition-based preconditioner. The software is written in C++ and is designed for use with massively parallel computers, using MPI. The algorithm is based on the FETI-DP method, with additional capabilities for handling constraint equations, as well as interfacing with the Salinas structural dynamics code and the Finite Element Interface (FEI) library. Practical Application: FETI Prime is designed for use with finite element-based simulation codes for solid and structural mechanics. The solver uses element matrices, connectivity information, nodal information, and force vectors computed by the host code and provides back the solution to the linear system of equations, to the user specified level of accuracy, The library is compiled with the host code and becomes an integral part of the host code executable.
Coarse-to-fine markerless gait analysis based on PCA and Gauss-Laguerre decomposition
NASA Astrophysics Data System (ADS)
Goffredo, Michela; Schmid, Maurizio; Conforto, Silvia; Carli, Marco; Neri, Alessandro; D'Alessio, Tommaso
2005-04-01
Human movement analysis is generally performed through the utilization of marker-based systems, which allow reconstructing, with high levels of accuracy, the trajectories of markers allocated on specific points of the human body. Marker based systems, however, show some drawbacks that can be overcome by the use of video systems applying markerless techniques. In this paper, a specifically designed computer vision technique for the detection and tracking of relevant body points is presented. It is based on the Gauss-Laguerre Decomposition, and a Principal Component Analysis Technique (PCA) is used to circumscribe the region of interest. Results obtained on both synthetic and experimental tests provide significant reduction of the computational costs, with no significant reduction of the tracking accuracy.
On the decomposition mechanisms of new imidazole-based energetic materials.
Yu, Zijun; Bernstein, Elliot R
2013-02-28
New imidazole-based energetic molecules (1,4-dinitroimidazole, 2,4-dinitroimidazole, 1-methyl-2,4-dinitroimidazole, and 1-methyl-2,4,5-trinitroimidazole) are studied both experimentally and theoretically. The NO molecule is observed as a main decomposition product from the above nitroimidazole energetic molecules excited at three UV wavelengths (226, 236, and 248 nm). Resolved rotational spectra related to three vibronic bands (0-0), (0-1), and (0-2) of the NO (A (2)Σ(+) ← X (2)Π) electronic transition have been obtained. A unique excitation wavelength independent dissociation channel is characterized for these four nitroimidazole energetic molecules: this pathway generates the NO product with a rotationally cold (10-60 K) and vibrationally hot (1300-1600 K) internal energy distribution. The predicted reaction mechanism for the nitroimidazole energetic molecule decomposition subsequent to electronic excitation is the following: electronically excited nitroimidazole energetic molecules descend to their ground electronic states through a series of conical intersections, dissociate on their ground electronic states subsequent to a nitro-nitrite isomerization, and produce NO molecules. Different from PETN, HMX, and RDX, the thermal dissociation process (ground electronic state decomposition from the Franck-Condon equilibrium point) of multinitroimidazoles is predicted to be a competition between NO(2) elimination and nitro-nitrite isomerization followed by NO elimination for all multinitroimidazoles except 1,4-dinitroimidazole. In this latter instance, N-NO(2) homolysisis becomes the dominant decomposition channel on the ground electronic state, as found for HMX and RDX. Comparison of the stability of nitro-containing energetic materials with R-NO(2) (R = C, N, O) moieties is also discussed. Energetic materials with C-NO(2) are usually more thermally stable and impact/shock insensitive than are other energetic materials with N-NO(2) and O-NO(2) moieties. The
Shang, Ming; Cao, Min; Wang, Qifan; Wasa, Masayuki
2017-09-05
An enantioselective direct Mannich-type reaction catalyzed by a sterically frustrated Lewis acid/Brønsted base complex is disclosed. Cooperative functioning of the chiral Lewis acid and achiral Brønsted base components gives rise to in situ enolate generation from monocarbonyl compounds. Subsequent reaction with hydrogen-bond-activated aldimines delivers β-aminocarbonyl compounds with high enantiomeric purity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Yu, Xuezhe; Li, Lixia; Wang, Hailong; Xiao, Jiaxing; Shen, Chao; Pan, Dong; Zhao, Jianhua
2016-05-19
For the epitaxial growth of Ga-based III-V semiconductor nanowires (NWs) on Si, Ga droplets could provide a clean and compatible solution in contrast to the common Au catalyst. However, the use of Ga droplets is rather limited except for that in Ga-catalyzed GaAs NW studies in a relatively narrow growth temperature (Ts) window around 620 °C on Si. In this paper, we have investigated the two-step growth of Ga-catalyzed III-V NWs on Si (111) substrates by molecular-beam epitaxy. First, by optimizing the surface oxide, vertically aligned GaAs NWs with a high yield are obtained at Ts = 620 °C. Then a two-temperature procedure is adopted to preserve Ga droplets at lower Ts, which leads to an extension of Ts down to 500 °C for GaAs NWs. Based on this procedure, systematic morphological and structural studies for Ga-catalyzed GaAs NWs in the largest Ts range could be presented. Then within the same growth scheme, for the first time, we demonstrate Ga-catalyzed GaAs/GaSb heterostructure NWs. These GaSb NWs are axially grown on the GaAs NW sections and are pure zinc-blende single crystals. Compositional measurements confirm that the catalyst particles indeed mainly consist of Ga and GaSb sections are of high purity but with a minor composition of As. In the end, we present GaAsSb NW growth with a tunable Sb composition. Our results provide useful information for the controllable synthesis of multi-compositional Ga-catalyzed III-V semiconductor NWs on Si for heterogeneous integration.
Wavelet decomposition based principal component analysis for face recognition using MATLAB
NASA Astrophysics Data System (ADS)
Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish
2016-03-01
For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.
Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach
NASA Technical Reports Server (NTRS)
Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil
2016-01-01
Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.
CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition
Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe
2013-01-01
Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764
Computationally Efficient Adaptive Beamformer for Ultrasound Imaging Based on QR Decomposition.
Park, Jongin; Wi, Seok-Min; Lee, Jin S
2016-02-01
Adaptive beamforming methods for ultrasound imaging have been studied to improve image resolution and contrast. The most common approach is the minimum variance (MV) beamformer which minimizes the power of the beamformed output while maintaining the response from the direction of interest constant. The method achieves higher resolution and better contrast than the delay-and-sum (DAS) beamformer, but it suffers from high computational cost. This cost is mainly due to the computation of the spatial covariance matrix and its inverse, which requires O(L(3)) computations, where L denotes the subarray size. In this study, we propose a computationally efficient MV beamformer based on QR decomposition. The idea behind our approach is to transform the spatial covariance matrix to be a scalar matrix σI and we subsequently obtain the apodization weights and the beamformed output without computing the matrix inverse. To do that, QR decomposition algorithm is used and also can be executed at low cost, and therefore, the computational complexity is reduced to O(L(2)). In addition, our approach is mathematically equivalent to the conventional MV beamformer, thereby showing the equivalent performances. The simulation and experimental results support the validity of our approach.
NASA Astrophysics Data System (ADS)
Ee, Tang Zo; Lim, Steven; Ling, Pang Yean; Huei, Wong Kam; Chyuan, Ong Hwai
2017-04-01
Experiment was carried out to study the feasibility of biomass derived solid acid catalyst for the production of biodiesel using Palm Fatty Acid Distillate (PFAD). Malaysia indigenous seaweed was selected as the biomass to be carbonized as the catalyst support. Sulfonation of seaweed based carbon material was carried out by thermal decomposition of ammonium sulfate, (NH4)2SO4. The effects of carbonization temperature at 200 to 600°C on the catalyst physical and chemical properties were studied. The effect of reaction parameters on the fatty acid methyl ester (FAME) yield was studied by varying the concentration of ammonium sulfate (5.0 to 40.0 w/v%) and thermal decomposition time (15 to 90 min). Characterizations of catalyst were carried out to study the catalyst surface morphology with Scanning Electron Microscope (SEM), acid density with back titration and functional group attached with FT-IR. Results showed that when the catalyst sulfonated with 10.0 w/v% ammonium sulfate solution and heated to 235°C for 30 min, the highest FAME yield achieved was 23.7% at the reaction condition of 5.0 wt.% catalyst loading, esterification time of 4 h, methanol to PFAD molar ratio of 20:1 at 100°C reaction temperature.
Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition
Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.
2015-01-01
A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714
Time-domain noise reduction based on an orthogonal decomposition for desired signal extraction.
Benesty, Jacob; Chen, Jingdong; Arden Huang, Yiteng; Gaensler, Tomas
2012-07-01
This paper addresses the problem of noise reduction in the time domain where the clean speech sample at every time instant is estimated by filtering a vector of the noisy speech signal. Such a clean speech estimate consists of both the filtered speech and residual noise (filtered noise) as the noisy vector is the sum of the clean speech and noise vectors. Traditionally, the filtered speech is treated as the desired signal after noise reduction. This paper proposes to decompose the clean speech vector into two orthogonal components: one is correlated and the other is uncorrelated with the current clean speech sample. While the correlated component helps estimate the clean speech, it is shown that the uncorrelated component interferes with the estimation, just as the additive noise. Based on this orthogonal decomposition, the paper presents a way to define the error signal and cost functions and addresses the issue of how to design different optimal noise reduction filters by optimizing these cost functions. Specifically, it discusses how to design the maximum SNR filter, the Wiener filter, the minimum variance distortionless response (MVDR) filter, the tradeoff filter, and the linearly constrained minimum variance (LCMV) filter. It demonstrates that the maximum SNR, Wiener, MVDR, and tradeoff filters are identical up to a scaling factor. It also shows from the orthogonal decomposition that many performance measures can be defined, which seem to be more appropriate than the traditional ones for the evaluation of the noise reduction filters.
Chen, Xiyuan; Wang, Wei
2017-05-01
Vibration is an important error source in fiber-optic gyroscopes (FOGs), and the extraction and compensation of vibration signals are important ways to eliminate the error and improve the accuracy of FOG. To decompose the vibration signal better, a new algorithm based on empirical mode decomposition (EMD) with masking signal is proposed in this paper. The masking signal is a kind of sinusoidal signal, and the frequency and amplitude of the masking signal are selected using improved particle swarm optimization. The proposed algorithm is called adaptive masking EMD (AM-EMD). First, the optimal frequency value and range of the masking signal are analyzed and presented. Then, an optimal decomposition of the vibration signal is obtained using the PSO to obtain the optimal frequency and amplitude of the masking signal. Finally, the extraction and compensation of the vibration signal are completed according to the mean value of intrinsic mode functions (IMFs) and the correlation coefficients between IMFs and the vibration signal. Experiments show that the new method can decompose the signal more accurately compared to traditional methods, and the precision of compensation is higher.
Mo, Yirong; Bao, Peng; Gao, Jiali
2011-04-21
An interaction energy decomposition analysis method based on the block-localized wavefunction (BLW-ED) approach is described. The first main feature of the BLW-ED method is that it combines concepts of valence bond and molecular orbital theories such that the intermediate and physically intuitive electron-localized states are variationally optimized by self-consistent field calculations. Furthermore, the block-localization scheme can be used both in wave function theory and in density functional theory, providing a useful tool to gain insights on intermolecular interactions that would otherwise be difficult to obtain using the delocalized Kohn-Sham DFT. These features allow broad applications of the BLW method to energy decomposition (BLW-ED) analysis for intermolecular interactions. In this perspective, we outline theoretical aspects of the BLW-ED method, and illustrate its applications in hydrogen-bonding and π-cation intermolecular interactions as well as metal-carbonyl complexes. Future prospects on the development of a multistate density functional theory (MSDFT) are presented, making use of block-localized electronic states as the basis configurations.
Bao, Peng
2013-01-01
An interaction energy decomposition analysis method based on the block-localized wavefunction (BLW-ED) approach is described. The first main feature of the BLW-ED method is that it combines concepts of valence bond and molecular orbital theories such that the intermediate and physically intuitive electron-localized states are variationally optimized by self-consistent field calculations. Furthermore, the block-localization scheme can be used both in wave function theory and in density functional theory, providing a useful tool to gain insights on intermolecular interactions that would otherwise be difficult to obtain using the delocalized Kohn–Sham DFT. These features allow broad applications of the BLW method to energy decomposition (BLW-ED) analysis for intermolecular interactions. In this perspective, we outline theoretical aspects of the BLW-ED method, and illustrate its applications in hydrogen-bonding and π–cation intermolecular interactions as well as metal–carbonyl complexes. Future prospects on the development of a multistate density functional theory (MSDFT) are presented, making use of block-localized electronic states as the basis configurations. PMID:21369567
Seasonal variations of MLT tides revealed by a meteor radar chain based on Hough mode decomposition
NASA Astrophysics Data System (ADS)
Yu, You; Wan, Weixing; Ren, Zhipeng; Xiong, Bo; Zhang, Yun; Hu, Lianhuan; Ning, Baiqi; Liu, Libo
2015-08-01
Seasonal variations of different tides in the mesosphere and lower thermosphere are investigated from wind observations of a meteor radar chain on the basis of Hough mode decomposition. First, the observed winds are decomposed into different (diurnal, semidiurnal, and terdiurnal) tidal components. Different seasonal patterns are revealed for each component. Pronounced semiannual oscillation (SAO) is presented in the diurnal component, while latitude-dependent seasonal variation is found in the semidiurnal and terdiurnal components. At the low/midlatitude stations, the semiannual/annual oscillation is relatively stronger. Then, Hough mode decomposition is utilized to extract the dominant tidal modes of each decomposed component. It is found that each component is dominated by one of its symmetric tidal modes with strong seasonal dependency. Apparent SAO is observed in the dominant (1, 1) mode; (2, 4) mode is strong in the autumn and winter months (after the September equinox). Based on the extracted results we further map the three-dimensional distribution (latitude × altitude × season) of each tidal component. The mapped results are finally compared with the corresponding values observed by the Thermosphere Ionosphere Mesosphere Energetics and Dynamics Doppler Interferometer (TIDI) and modeled from the global scale wave model (GSWM). Each mapped tidal component agrees well with corresponding TIDI observation in the seasonal variation. Meanwhile, coincidences are found in the seasonal dependency of the diurnal component between the mapped values and the modeled results from GSWM, while difference between them exists in that of the semidiurnal one.
Decomposition-Based Failure Mode Identification Method for Risk-Free Design of Large Systems
NASA Technical Reports Server (NTRS)
Tumer, Irem Y.; Stone, Robert B.; Roberts, Rory A.; Clancy, Daniel (Technical Monitor)
2002-01-01
When designing products, it is crucial to assure failure and risk-free operation in the intended operating environment. Failures are typically studied and eliminated as much as possible during the early stages of design. The few failures that go undetected result in unacceptable damage and losses in high-risk applications where public safety is of concern. Published NASA and NTSB accident reports point to a variety of components identified as sources of failures in the reported cases. In previous work, data from these reports were processed and placed in matrix form for all the system components and failure modes encountered, and then manipulated using matrix methods to determine similarities between the different components and failure modes. In this paper, these matrices are represented in the form of a linear combination of failures modes, mathematically formed using Principal Components Analysis (PCA) decomposition. The PCA decomposition results in a low-dimensionality representation of all failure modes and components of interest, represented in a transformed coordinate system. Such a representation opens the way for efficient pattern analysis and prediction of failure modes with highest potential risks on the final product, rather than making decisions based on the large space of component and failure mode data. The mathematics of the proposed method are explained first using a simple example problem. The method is then applied to component failure data gathered from helicopter, accident reports to demonstrate its potential.
Anomaly detection in hyperspectral imagery based on low-rank and sparse decomposition
NASA Astrophysics Data System (ADS)
Cui, Xiaoguang; Tian, Yuan; Weng, Lubin; Yang, Yiping
2014-01-01
This paper presents a novel low-rank and sparse decomposition (LSD) based model for anomaly detection in hyperspectral images. In our model, a local image region is represented as a low-rank matrix plus spares noises in the spectral space, where the background can be explained by the low-rank matrix, and the anomalies are indicated by the sparse noises. The detection of anomalies in local image regions is formulated as a constrained LSD problem, which can be solved efficiently and robustly with a modified "Go Decomposition" (GoDec) method. To enhance the validity of this model, we adapts a "simple linear iterative clustering" (SLIC) superpixel algorithm to efficiently generate homogeneous local image regions i.e. superpixels in hyperspectral imagery, thus ensures that the background in local image regions satisfies the condition of low-rank. Experimental results on real hyperspectral data demonstrate that, compared with several known local detectors including RX detector, kernel RX detector, and SVDD detector, the proposed model can comfortably achieves better performance in satisfactory computation time.
Jiang, Yi; Woortman, Albert J.J.; Alberda van Ekenstein, Gert O.R.; Loos, Katja
2013-01-01
Bio-based commercially available succinate, itaconate and 1,4-butanediol are enzymatically co-polymerized in solution via a two-stage method, using Candida antarctica Lipase B (CALB, in immobilized form as Novozyme® 435) as the biocatalyst. The chemical structures of the obtained products, poly(butylene succinate) (PBS) and poly(butylene succinate-co-itaconate) (PBSI), are confirmed by 1H- and 13C-NMR. The effects of the reaction conditions on the CALB-catalyzed synthesis of PBSI are fully investigated, and the optimal polymerization conditions are obtained. With the established method, PBSI with tunable compositions and satisfying reaction yields is produced. The 1H-NMR results confirm that carbon-carbon double bonds are well preserved in PBSI. The differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA) results indicate that the amount of itaconate in the co-polyesters has no obvious effects on the glass-transition temperature and the thermal stability of PBS and PBSI, but has significant effects on the melting temperature. PMID:24970176
Jiang, Yi; Woortman, Albert J J; van Ekenstein, Gert O R Alberda; Loos, Katja
2013-08-12
Bio-based commercially available succinate, itaconate and 1,4-butanediol are enzymatically co-polymerized in solution via a two-stage method, using Candida antarctica Lipase B (CALB, in immobilized form as Novozyme® 435) as the biocatalyst. The chemical structures of the obtained products, poly(butylene succinate) (PBS) and poly(butylene succinate-co-itaconate) (PBSI), are confirmed by 1H- and 13C-NMR. The effects of the reaction conditions on the CALB-catalyzed synthesis of PBSI are fully investigated, and the optimal polymerization conditions are obtained. With the established method, PBSI with tunable compositions and satisfying reaction yields is produced. The 1H-NMR results confirm that carbon-carbon double bonds are well preserved in PBSI. The differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA) results indicate that the amount of itaconate in the co-polyesters has no obvious effects on the glass-transition temperature and the thermal stability of PBS and PBSI, but has significant effects on the melting temperature.
NASA Astrophysics Data System (ADS)
Elharrouss, Omar; Moujahid, Driss; Elkah, Samah; Tairi, Hamid
2016-11-01
A particular algorithm for moving object detection using a background subtraction approach is proposed. We generate the background model by combining quad-tree decomposition with entropy theory. In general, many background subtraction approaches are sensitive to sudden illumination change in the scene and cannot update the background image in scenes. The proposed background modeling approach analyzes the illumination change problem. After performing the background subtraction based on the proposed background model, the moving targets can be accurately detected at each frame of the image sequence. In order to produce high accuracy for the motion detection, the binary motion mask can be computed by the proposed threshold function. The experimental analysis based on statistical measurements proves the efficiency of our proposed method in terms of quality and quantity. And it even outperforms substantially existing methods by perceptional evaluation.
An infrared target detection algorithm based on lateral inhibition and singular value decomposition
NASA Astrophysics Data System (ADS)
Li, Yun; Song, Yong; Zhao, Yufei; Zhao, Shangnan; Li, Xu; Li, Lin; Tang, Songyuan
2017-09-01
This paper proposes an infrared target detection algorithm based on lateral inhibition (LI) and singular value decomposition (SVD). Firstly, a local structure descriptor based on SVD of gradient domain is constructed, which reflects basic structures of the local regions of an infrared image. Then, LI network is modified by combining LI with the local structure descriptor for enhancing target and suppressing background. Meanwhile, to calculate lateral inhibition coefficients adaptively, the direction parameters are determined by the dominant orientations obtained from SVD. Experimental results show that, compared with the typical algorithms, the proposed algorithm not only can detect small target or area target under complex backgrounds, but also has excellent abilities of background suppression and target enhancement.
NASA Astrophysics Data System (ADS)
Huang, X. Y.; Zhou, J. Q.; Wang, Z.; Deng, L. C.; Hong, S.
2017-05-01
China is now at a stage of accelerated industrialization and urbanization, with energy-intensive industries contributing a large proportion of economic growth. In this study, we examined industrial energy consumption by decomposition analysis to describe the driving factors of energy consumption in China. Based on input-output (I-O) tables from the World Input-Output Database (WIOD) website and China’s energy use data from 1995 to 2011, we studied the sectorial changes of energy efficiency during the examined period. The results showed that all industries increased their energy efficiency. Energy consumption was decomposed into three factors by the logarithmic mean Divisia index (LMDI) method. The increase in production output was the leading factor that drives up China’s energy consumption. World Trade Organization accession and financial crises had great impact on the energy consumption. Based on these results, a series of energy policy suggestions for decision-makers has been proposed.
NASA Astrophysics Data System (ADS)
Cai, Jianjun; Shen, Xueju
2017-10-01
We propose a modified optical asymmetric cryptosystem based on coherent superposition and equal modulus decomposition (EMD). In the encryption process, the asymmetric cells of the previous cryptosystem is cascaded, while some small changes are made. In the first cell, only one mask, whose phase is not equal with the public key, is generated to be used as the input of the second cell. As a consequence, the modified cryptosystem decreases available constrain conditions for attackers, resulting in a high robustness of the cryptosystem against the attack based on iterative Fourier transform. Furthermore, the modified scheme maintains the good performance of our previous cryptosystem, especially the benefit of key management. Some numerical simulations are presented to verify the validity and the performance of the modified cryptosystem.
New Denoising Method Based on Empirical Mode Decomposition and Improved Thresholding Function
NASA Astrophysics Data System (ADS)
Mohguen, Wahiba; RaïsEl'hadiBekka
2017-01-01
This paper presents a new denoising method called EMD-ITF that was based on Empirical Mode Decomposition (EMD) and the Improved Thresholding Function (ITF) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs were thresholded by applying the improved thresholding function to suppress noise and improve the signal to noise ratio (SNR). The method was tested on simulated and real data and the results were compared to the EMD-Based signal denoising methods using the soft thresholding. The results showed the superior performance of the new EMD-ITF denoising over the traditional approach. The performance were evaluated in terms of SNR in dB, and Mean Square Error (MSE).
NASA Astrophysics Data System (ADS)
Riasati, Vahid R.
2016-05-01
In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.
NASA Astrophysics Data System (ADS)
Rönkkö, Mikko; Frühwirth, Christian; Biffl, Stefan
Value-based software engineering (VBSE) is an emerging stream of research that addresses the value considerations of software and extends the traditional scope of software engineering from technical issues to business-relevant decision problems. While the concept of value in VBSE relies on the well-established economic value concept, the exact definition for this key concept within VBSE domain is still not well defined or agreed upon. We argue the discourse on value can significantly benefit from drawing from research in management, particularly software business. In this paper, we present three aspects of software: as a technology, as a design, and as an artifact. Furthermore, we divide the value concept into three components that are relevant for software product development companies and their customers: intrinsic value, externalities and option value. Finally, we propose a value decomposition matrix based on technology views and value components.
In the late 1970s thousands of gallons of transformer fluid contaminated with PCBs were illegally sprayed along approximately 210 miles of North Carolina state roadways. Listed as a Superfund site, the contaminated roadway berms were excavated and disposed in an approved PCB land...
In the late 1970s thousands of gallons of transformer fluid contaminated with PCBs were illegally sprayed along approximately 210 miles of North Carolina state roadways. Listed as a Superfund site, the contaminated roadway berms were excavated and disposed in an approved PCB land...
NASA Astrophysics Data System (ADS)
Niu, G.; Zhang, X.; Barron-Gafford, G.; Pavao-zuckerman, M.
2013-12-01
Soil respiration pulses in response to pulsed wetting ('Birch effect'; Birch 1958) have long been observed from laboratory and field experiments. The Birch effect produces more CO2 efflux and sustains greater microbial biomass than constantly moist soils. Various mechanisms causing the effect have been proposed. However, the exact mechanism underlying the Birch effect is not clear, and thus most models are not able to simulate this effect. We have recently developed a microbial enzyme based decomposition and gas transport model. The model integrates the most recent advances in the understanding of critical processes, including enzyme-catalyzed degradation of soil organic carbon (SOC) to dissolved organic carbon (DOC), acclimation of carbon use efficiency (CUE) for the uptake of DOC by microbes, and diffusive and convective transport of O2 and CO2 in the soil. The model has four kinds of carbon pools including SOC, DOC, microbial biomass (MIC), and extracellular enzyme (ENZ). However, the model coupled with a land surface model, which accurately simulates soil moisture and temperature, failed to simulate the Birch effect observed at a natural savannah ecosystem site in the southwest US monsoon region. We further divided the DOC and ENZ pools into two sub-pools, one for a wet zone and the other for a dry zone, respectively. We assume that in the dry zone, DOC can be produced through enzyme catalysis, although at a lower rate due to enzyme immobilization, and only in the wet zone can microbes take up DOC. Thus, the modeled DOC accumulates during dry periods and is quickly transitioned into DOC in the wet zone (proportional to saturation) in response to pulsed wetting during a storm, and becomes available for microbial use. In such a way, the model successfully simulates the Birch effect with the Nash-Sutcliffe model efficiency being ~ 0.75 (correlation coefficient ~ 0.88) at a half-hourly time step. We will also present the effect of gas transport on the Birch effect
Denmark, Scott E; Baird, John D
2006-06-23
This paper chronicles the conceptual development, proof of principle experiments, and recent advances in the palladium-catalyzed cross-coupling reactions of the conjugate bases of organosilanols. The discovery that led to the design and refinement of this process represents a classical illustration of how mechanistic studies can provide a fertile ground for the invention of new reactions. On the basis of a working hypothesis (which ultimately proved to be incorrect) and the desire to effect silicon-based cross-coupling without the agency of fluoride activation, a mild and practical palladium-catalyzed cross-coupling of alkenyl-, aryl-, and heteroaryl silanolates has been developed. The mechanistic underpinnings, methodological extensions, and the successful applications of this technology to the synthesis of complex molecules are described.
Analysis of Human's Motions Based on Local Mean Decomposition in Through-wall Radar Detection
NASA Astrophysics Data System (ADS)
Lu, Qi; Liu, Cai; Zeng, Zhaofa; Li, Jing; Zhang, Xuebing
2016-04-01
Observation of human motions through a wall is an important issue in security applications and search-and rescue. Radar has advantages in looking through walls where other sensors give low performance or cannot be used at all. Ultrawideband (UWB) radar has high spatial resolution as a result of employment of ultranarrow pulses. It has abilities to distinguish the closely positioned targets and provide time-lapse information of targets. Moreover, the UWB radar shows good performance in wall penetration when the inherently short pulses spread their energy over a broad frequency range. Human's motions show periodic features including respiration, swing arms and legs, fluctuations of the torso. Detection of human targets is based on the fact that there is always periodic motion due to breathing or other body movements like walking. The radar can gain the reflections from each human body parts and add the reflections at each time sample. The periodic movements will cause micro-Doppler modulation in the reflected radar signals. Time-frequency analysis methods are consider as the effective tools to analysis and extract micro-Doppler effects caused by the periodic movements in the reflected radar signal, such as short-time Fourier transform (STFT), wavelet transform (WT), and Hilbert-Huang transform (HHT).The local mean decomposition (LMD), initially developed by Smith (2005), is to decomposed amplitude and frequency modulated signals into a small set of product functions (PFs), each of which is the product of an envelope signal and a frequency modulated signal from which a time-vary instantaneous phase and instantaneous frequency can be derived. As bypassing the Hilbert transform, the LMD has no demodulation error coming from window effect and involves no negative frequency without physical sense. Also, the instantaneous attributes obtained by LMD are more stable and precise than those obtained by the empirical mode decomposition (EMD) because LMD uses smoothed local
Kinetics and mechanism of the base-catalyzed rearrangement and hydrolysis of ezetimibe.
Baťová, Jana; Imramovský, Aleš; HájÍček, Josef; Hejtmánková, Ludmila; Hanusek, Jiří
2014-08-01
The pH-rate profile of the pseudo-first-order rate constants for the rearrangement and hydrolysis of Ezetimibe giving (2R,3R,6S)-N,6-bis(4-fluorophenyl)-2-(4-hydroxyphenyl)-3,4,5,6-tetrahydro-2H-pyran-3-carboxamide (2) as the main product at pH of less than 12.5 and the mixture of 2 and 5-(4-fluorophenyl)-5-hydroxy-2-[(4-fluorophenylamino)-(4-hydroxyphenyl)methyl]-pentanoic acid (3) at pH of more than 12.5 in aqueous tertiary amine buffers and in sodium hydroxide solutions at ionic strength I = 0.1 mol L(-1) (KCl) and at 39 °C is reported. No buffer catalysis was observed and only specific base catalysis is involved. The pH-rate profile is more complex than the pH-rate profiles for the hydrolysis of simple β-lactams and it contains several breaks. Up to pH 9, the log k(obs) linearly increases with pH, but between pH 9 and 11 a distinct break downwards occurs and the values of log k(obs) slightly decrease with increasing pH of the medium. At pH of approximately 13, another break upwards occurs that corresponds to the formation of compound 3 that is slowly converted to (2R,3R,6S)-6-(4-fluorophenyl)-2-(4-hydroxyphenyl)-3,4,5,6-tetrahydro-2H-pyran-3-carboxylic acid (4). The kinetics of base-catalyzed hydrolysis of structurally similar azetidinone is also discussed.
Optimization-based additive decomposition of weakly coercive problems with applications
Bochev, Pavel B.; Ridzal, Denis
2016-01-27
In this study, we present an abstract mathematical framework for an optimization-based additive decomposition of a large class of variational problems into a collection of concurrent subproblems. The framework replaces a given monolithic problem by an equivalent constrained optimization formulation in which the subproblems define the optimization constraints and the objective is to minimize the mismatch between their solutions. The significance of this reformulation stems from the fact that one can solve the resulting optimality system by an iterative process involving only solutions of the subproblems. Consequently, assuming that stable numerical methods and efficient solvers are available for every subproblem,more » our reformulation leads to robust and efficient numerical algorithms for a given monolithic problem by breaking it into subproblems that can be handled more easily. An application of the framework to the Oseen equations illustrates its potential.« less
NASA Astrophysics Data System (ADS)
Dong, Lieqian; Wang, Deying; Zhang, Yimeng; Zhou, Datong
2017-09-01
Signal enhancement is a necessary step in seismic data processing. In this paper we utilize the complementary ensemble empirical mode decomposition (CEEMD) and complex curvelet transform (CCT) methods to separate signal from random noise further to improve the signal to noise (S/N) ratio. Firstly, the original data with noise is decomposed into a series of intrinsic mode function (IMF) profiles with the aid of CEEMD. Then the IMFs with noise are transformed into CCT domain. By choosing different thresholds which are based on the noise level difference of each IMF profile, the noise in original data can be suppressed. Finally, we illustrate the effectiveness of the approach by simulated and field datasets.
A Human ECG Identification System Based on Ensemble Empirical Mode Decomposition
Zhao, Zhidong; Yang, Lei; Chen, Diandian; Luo, Yi
2013-01-01
In this paper, a human electrocardiogram (ECG) identification system based on ensemble empirical mode decomposition (EEMD) is designed. A robust preprocessing method comprising noise elimination, heartbeat normalization and quality measurement is proposed to eliminate the effects of noise and heart rate variability. The system is independent of the heart rate. The ECG signal is decomposed into a number of intrinsic mode functions (IMFs) and Welch spectral analysis is used to extract the significant heartbeat signal features. Principal component analysis is used reduce the dimensionality of the feature space, and the K-nearest neighbors (K-NN) method is applied as the classifier tool. The proposed human ECG identification system was tested on standard MIT-BIH ECG databases: the ST change database, the long-term ST database, and the PTB database. The system achieved an identification accuracy of 95% for 90 subjects, demonstrating the effectiveness of the proposed method in terms of accuracy and robustness. PMID:23698274
Riemann Liouvelle Fractional Integral based Empirical Mode Decomposition for ECG Denoising.
Jain, Shweta; Bajaj, Varun; Kumar, Anil
2017-09-18
Electrocardiograph (ECG) denoising is the most important step in diagnosis of heart related diseases, as the diagnosis gets influenced with noises. In this paper, a new method for ECG denoising is proposed, which incorporates empirical mode decomposition algorithm and Riemann Liouvelle (RL) fractional integral filtering. In the proposed method, noisy ECG signal is decomposed into its intrinsic mode functions (IMFs); from which noisy IMFs are identified by proposed noisy-IMFs identification methodology. RL fractional integral filtering is applied on noisy IMFs to get denoised IMFs; ECG signal is reconstructed with denoised IMFs and remaining signal dominant IMFs to obtain noise-free ECG signal. Proposed methodology is tested with MIT-BIH arrhythmia database. Its performance, in terms of signal to noise ratio (SNR) and mean square error (MSE), is compared with other related fractional integral and EMD based ECG denoising methods. The obtained results by proposed method prove that the proposed method gives efficient noise removal performance.
Stoica, Petre; Sandgren, Niclas; Selén, Yngve; Vanhamme, Leentje; Van Huffel, Sabine
2003-11-01
In several applications of NMR spectroscopy the user is interested only in the components lying in a small frequency band of the spectrum. A frequency selective analysis deals precisely with this kind of NMR spectroscopy: parameter estimation of only those spectroscopic components that lie in a preselected frequency band of the NMR data spectrum, with as little interference as possible from the out-of-band components and in a computationally efficient way. In this paper we introduce a frequency-domain singular value decomposition (SVD)-based method for frequency selective spectroscopy that is computationally simple, statistically accurate, and which has a firm theoretical basis. To illustrate the good performance of the proposed method we present a number of numerical examples for both simulated and in vitro NMR data.
NASA Astrophysics Data System (ADS)
Li, Hongguang; Li, Ming; Li, Cheng; Li, Fucai; Meng, Guang
2017-09-01
This paper dedicates on the multi-faults decoupling of turbo-expander rotor system using Differential-based Ensemble Empirical Mode Decomposition (DEEMD). DEEMD is an improved version of DEMD to resolve the imperfection of mode mixing. The nonlinear behaviors of the turbo-expander considering temperature gradient with crack, rub-impact and pedestal looseness faults are investigated respectively, so that the baseline for the multi-faults decoupling can be established. DEEMD is then utilized on the vibration signals of the rotor system with coupling faults acquired by numerical simulation, and the results indicate that DEEMD can successfully decouple the coupling faults, which is more efficient than EEMD. DEEMD is also applied on the vibration signal of the misalignment coupling with rub-impact fault obtained during the adjustment of the experimental system. The conclusion shows that DEEMD can decompose the practical multi-faults signal and the industrial prospect of DEEMD is verified as well.
Trading strategy based on dynamic mode decomposition: Tested in Chinese stock market
NASA Astrophysics Data System (ADS)
Cui, Ling-xiao; Long, Wen
2016-11-01
Dynamic mode decomposition (DMD) is an effective method to capture the intrinsic dynamical modes of complex system. In this work, we adopt DMD method to discover the evolutionary patterns in stock market and apply it to Chinese A-share stock market. We design two strategies based on DMD algorithm. The strategy which considers only timing problem can make reliable profits in a choppy market with no prominent trend while fails to beat the benchmark moving-average strategy in bull market. After considering the spatial information from spatial-temporal coherent structure of DMD modes, we improved the trading strategy remarkably. Then the DMD strategies profitability is quantitatively evaluated by performing SPA test to correct the data-snooping effect. The results further prove that DMD algorithm can model the market patterns well in sideways market.
Wu, Zhizhang Huang, Zhongyi
2016-07-15
In this paper, we consider the numerical solution of the one-dimensional Schrödinger equation with a periodic lattice potential and a random external potential. This is an important model in solid state physics where the randomness results from complicated phenomena that are not exactly known. Here we generalize the Bloch decomposition-based time-splitting pseudospectral method to the stochastic setting using the generalized polynomial chaos with a Galerkin procedure so that the main effects of dispersion and periodic potential are still computed together. We prove that our method is unconditionally stable and numerical examples show that it has other nice properties and is more efficient than the traditional method. Finally, we give some numerical evidence for the well-known phenomenon of Anderson localization.
Optimization-based additive decomposition of weakly coercive problems with applications
Bochev, Pavel B.; Ridzal, Denis
2016-01-27
In this study, we present an abstract mathematical framework for an optimization-based additive decomposition of a large class of variational problems into a collection of concurrent subproblems. The framework replaces a given monolithic problem by an equivalent constrained optimization formulation in which the subproblems define the optimization constraints and the objective is to minimize the mismatch between their solutions. The significance of this reformulation stems from the fact that one can solve the resulting optimality system by an iterative process involving only solutions of the subproblems. Consequently, assuming that stable numerical methods and efficient solvers are available for every subproblem, our reformulation leads to robust and efficient numerical algorithms for a given monolithic problem by breaking it into subproblems that can be handled more easily. An application of the framework to the Oseen equations illustrates its potential.
Bischof, C.; Sun, X.; Huss-Lederman, S.; Tsao, A.; Turnbull, T.
1994-06-01
In this paper, we discuss work in progress on a complete eigensolver based on the Invariant Subspace Decomposition Algorithm for dense symmetric matrices (SYISDA). We describe a recently developed acceleration technique that substantially reduces the overall work required by this algorithm and review the algorithmic highlights of a distributed-memory implementation of this approach. These include a fast matrix-matrix multiplication algorithm, a new approach to parallel band reduction and tridiagonalization, and a harness for coordinating the divide-and-conquer parallelism in the problem. We present performance results for the dominant kernel, dense matrix multiplication, as well as for the overall SYISDA implementation on the Intel Touchstone Delta and the Intel Paragon.
Abudu Rexit, Abulikemu; Luo, Shiwei; Mailikezati, Maihemuti
2016-11-18
A chiral phosphoric acid-catalyzed one-pot enantioselective reductive amination of 2-pyridyl ketones was realized to provide chiral pyridine-based ligands in excellent yields with high enantioselectivities (up to 98% yield, 94% ee). Computational studies on the key intermediate imine and transition state of the hydride transfer process revealed that the nitrogen atom of the pyridyl ring might be an important factor to significantly promote both the reaction activity and enantioselectivity.
Wang, Zhen-Yu; Ban, Shu-Rong; Yang, Meng-Chen; Li, Qing-Shan
2016-11-01
Organocatalysis and aqueous reactions are identified as the focus of the greening of chemistry. Combining these two strategies effectively remains an interesting challenge in organic synthesis. Herein, we used pyrrolidine-based benzoylthiourea 1c to catalyze the asymmetric Michael addition of cyclohexanone to various nitroolefins in water to afford the corresponding compounds in moderate to good yields, and with excellent diastereoselectivities (up to >99:1 dr) and enantioselectivities (up to 99% ee).
Mi, Le; Qin, Dandan; Cheng, Jie; Wang, Dan; Li, Sha; Wei, Xuetuan
2017-03-01
Two engineered Escherichia coli strains, DQ101 (MG1655 fadD (-))/pDQTES and DQ101 (MG1655 fadD (-))/pDQTESZ were constructed to investigate the free fatty acid production using ionic liquid-based acid- or enzyme-catalyzed bamboo hydrolysate as carbon source in this study. The plasmid, pDQTES, carrying an acyl-ACP thioesterase 'TesA of E. coli in pTrc99A was constructed firstly, and then (3R)-hydroxyacyl-ACP dehydratase was ligated after the TesA to give the plasmid pDQTESZ. These two strains exhibited efficient fatty acid production when glucose was used as the sole carbon source, with a final concentration of 2.45 and 3.32 g/L, respectively. The free fatty acid production of the two strains on xylose is not as efficient as that on glucose, which was 2.32 and 2.96 g/L, respectively. For mixed sugars, DQ101 (MG1655 fadD (-))-based strains utilized glucose and pentose sequentially under the carbon catabolite repression (CCR) regulation. The highest total FFAs concentration from the mixed sugar culture reached 2.81 g/L by DQ101 (MG1655 fadD (-))/pDQTESZ. Furthermore, when ionic liquid-based enzyme-catalyzed bamboo hydrolysate was used as the carbon source, the strain DQ101 (MG1655 fadD (-))/pDQTESZ could produce 1.23 g/L FFAs with a yield of 0.13 g/g, and while it just produced 0.65 g/L free fatty acid with the ionic liquid-based acid-catalyzed bamboo hydrolysate as the feedstock. The results suggested that enzymatic catalyzed bamboo hydrolysate with ionic liquid pretreatment could serve as an efficient feedstock for free fatty acid production.
Sakakura, Akira; Sakuma, Masayuki; Ishihara, Kazuaki
2011-06-17
Chiral Lewis base-assisted Brønsted acids (Chiral LBBAs) have been designed as new organocatalysts for biomimetic enantioselective cyclization. A salt of a chiral phosphonous acid diester with FSO(3)H catalyzes the enantioselective cyclization of 2-geranylphenols to give the desired trans-fused cyclized products with high diastereo- and enantioselectivities (up to 98:2 dr and 93% ee). © 2011 American Chemical Society
NASA Astrophysics Data System (ADS)
Peng, Fuqiang; Yu, Dejie; Luo, Jiesi
2011-02-01
Based on the chirplet path pursuit and the sparse signal decomposition method, a new sparse signal decomposition method based on multi-scale chirplet is proposed and applied to the decomposition of vibration signals from gearboxes in fault diagnosis. An over-complete dictionary with multi-scale chirplets as its atoms is constructed using the method. Because of the multi-scale character, this method is superior to the traditional sparse signal decomposition method wherein only a single scale is adopted, and is more applicable to the decomposition of non-stationary signals with multi-components whose frequencies are time-varying. When there are faults in a gearbox, the vibration signals collected are usually AM-FM signals with multiple components whose frequencies vary with the rotational speed of the shaft. The meshing frequency and modulating frequency, which vary with time, can be derived by the proposed method and can be used in gearbox fault diagnosis under time-varying shaft-rotation speed conditions, where the traditional signal processing methods are always blocked. Both simulations and experiments validate the effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Guo, Wei; Tse, Peter W.
2013-01-01
Today, remote machine condition monitoring is popular due to the continuous advancement in wireless communication. Bearing is the most frequently and easily failed component in many rotating machines. To accurately identify the type of bearing fault, large amounts of vibration data need to be collected. However, the volume of transmitted data cannot be too high because the bandwidth of wireless communication is limited. To solve this problem, the data are usually compressed before transmitting to a remote maintenance center. This paper proposes a novel signal compression method that can substantially reduce the amount of data that need to be transmitted without sacrificing the accuracy of fault identification. The proposed signal compression method is based on ensemble empirical mode decomposition (EEMD), which is an effective method for adaptively decomposing the vibration signal into different bands of signal components, termed intrinsic mode functions (IMFs). An optimization method was designed to automatically select appropriate EEMD parameters for the analyzed signal, and in particular to select the appropriate level of the added white noise in the EEMD method. An index termed the relative root-mean-square error was used to evaluate the decomposition performances under different noise levels to find the optimal level. After applying the optimal EEMD method to a vibration signal, the IMF relating to the bearing fault can be extracted from the original vibration signal. Compressing this signal component obtains a much smaller proportion of data samples to be retained for transmission and further reconstruction. The proposed compression method were also compared with the popular wavelet compression method. Experimental results demonstrate that the optimization of EEMD parameters can automatically find appropriate EEMD parameters for the analyzed signals, and the IMF-based compression method provides a higher compression ratio, while retaining the bearing defect
Hong, Danfeng; Su, Jian; Hong, Qinggen; Pan, Zhenkuan; Wang, Guodong
2014-01-01
As palmprints are captured using non-contact devices, image blur is inevitably generated because of the defocused status. This degrades the recognition performance of the system. To solve this problem, we propose a stable-feature extraction method based on a Vese-Osher (VO) decomposition model to recognize blurred palmprints effectively. A Gaussian defocus degradation model is first established to simulate image blur. With different degrees of blurring, stable features are found to exist in the image which can be investigated by analyzing the blur theoretically. Then, a VO decomposition model is used to obtain structure and texture layers of the blurred palmprint images. The structure layer is stable for different degrees of blurring (this is a theoretical conclusion that needs to be further proved via experiment). Next, an algorithm based on weighted robustness histogram of oriented gradients (WRHOG) is designed to extract the stable features from the structure layer of the blurred palmprint image. Finally, a normalized correlation coefficient is introduced to measure the similarity in the palmprint features. We also designed and performed a series of experiments to show the benefits of the proposed method. The experimental results are used to demonstrate the theoretical conclusion that the structure layer is stable for different blurring scales. The WRHOG method also proves to be an advanced and robust method of distinguishing blurred palmprints. The recognition results obtained using the proposed method and data from two palmprint databases (PolyU and Blurred-PolyU) are stable and superior in comparison to previous high-performance methods (the equal error rate is only 0.132%). In addition, the authentication time is less than 1.3 s, which is fast enough to meet real-time demands. Therefore, the proposed method is a feasible way of implementing blurred palmprint recognition.
Barma, Shovan; Chen, Bo-Wei; Ji, Wen; Rho, Seungmin; Chou, Chih-Hung; Wang, Jhing-Fa
2016-08-01
This study presents a precise way to detect the third ( S3 ) heart sound, which is recognized as an important indication of heart failure, based on nonlinear single decomposition and time-frequency localization. The detection of the S3 is obscured due to its significantly low energy and frequency. Even more, the detected S3 may be misunderstood as an abnormal second heart sound with a fixed split, which was not addressed in the literature. To detect such S3, the Hilbert vibration decomposition method is applied to decompose the heart sound into a certain number of subcomponents while intactly preserving the phase information. Thus, the time information of all of the decomposed components are unchanged, which further expedites the identification and localization of any module/section of a signal properly. Next, the proposed localization step is applied to the decomposed subcomponents by using smoothed pseudo Wigner-Ville distribution followed by the reassignment method. Finally, based on the positional information, the S3 is distinguished and confirmed by measuring time delays between the S2 and S3. In total, 82 sets of cardiac cycles collected from different databases including Texas Heart Institute database are examined for evaluation of the proposed method. The result analysis shows that the proposed method can detect the S3 correctly, even when the normalized temporal energy of S3 is larger than 0.16, and the frequency of those is larger than 34 Hz. In a performance analysis, the proposed method demonstrates that the accuracy rate of S3 detection is as high as 93.9%, which is significantly higher compared with the other methods. Such findings prove the robustness of the proposed idea for detecting substantially low-energized S3 .
Corona-Martínez, David Octavio; Gomez-Tagle, Paola; Yatsimirsky, Anatoly K
2012-10-19
Kinetics of transesterification of the RNA model substrate 2-hydroxypropyl 4-nitrophenyl phosphate promoted by Mg(2+) and Ca(2+), the most common biological metals acting as cofactors for nuclease enzymes and ribozymes, as well as by Co(NH(3))(6)(3+), Co(en)(3)(3+), Li(+), and Na(+) cations, often employed as mechanistic probes, was studied in 80% v/v (50 mol %) aqueous DMSO, a medium that allows one to discriminate easily specific base (OH(-)-catalyzed) and general base (buffer-catalyzed) reaction paths. All cations assist the specific base reaction, but only Mg(2+) and Na(+) assist the general base reaction. For Mg(2+)-assisted reactions, the solvent deuterium isotope effects are 1.23 and 0.25 for general base and specific base mechanisms, respectively. Rate constants for Mg(2+)-assisted general base reactions measured with different bases fit the Brønsted correlation with a slope of 0.38, significantly lower than the slope for the unassisted general base reaction (0.77). Transition state binding constants for catalysts in the specific base reaction (K(‡)(OH)) both in aqueous DMSO and pure water correlate with their binding constants to 4-nitrophenyl phosphate dianion (K(NPP)) used as a minimalist transition state model. It was found that K(‡)(OH) ≈ K(NPP) for "protic" catalysts (Co(NH(3))(6)(3+), Co(en)(3)(3+), guanidinium), but K(‡)(OH) ≫ K(NPP) for Mg(2+) and Ca(2+) acting as Lewis acids. It appears from results of this study that Mg(2+) is unique in its ability to assist efficiently the general base-catalyzed transesterification often occurring in active sites of nuclease enzymes and ribozymes.
NASA Astrophysics Data System (ADS)
Chen, Huasong; Qu, Xiangju; Jin, Ying; Li, Zhenhua; He, Anzhi
2016-10-01
Image deblurring is a fundamental problem in image processing. Conventional methods often deal with the degraded image as a whole while ignoring that an image contains two different components: cartoon and texture. Recently, total variation (TV) based image decomposition methods are introduced into image deblurring problem. However, these methods often suffer from the well-known stair-casing effects of TV. In this paper, a new cartoon -texture based sparsity regularization method is proposed for non-blind image deblurring. Based on image decomposition, it respectively regularizes the cartoon with a combined term including framelet-domain-based sparse prior and a quadratic regularization and the texture with the sparsity of discrete cosine transform domain. Then an adaptive alternative split Bregman iteration is proposed to solve the new multi-term sparsity regularization model. Experimental results demonstrate that our method can recover both cartoon and texture of images simultaneously, and therefore can improve the visual effect, the PSNR and the SSIM of the deblurred image efficiently than TV and the undecomposed methods.
Maass, Clemens; Baer, Matthias; Kachelriess, Marc
2009-08-01
Dual energy CT (DECT) measures the object of interest using two different x-ray spectra in order to provide energy-selective CT images or in order to get the material decomposition of the object. Today, two decomposition techniques are known. Image-based DECT uses linear combinations of reconstructed images to get an image that contains material-selective DECT information. Rawdata-based DECT correctly treats the available information by passing the rawdata through a decomposition function that uses information from both rawdata sets to create DECT specific (e.g., material-selective) rawdata. Then the image reconstruction yields material-selective images. Rawdata-based image decomposition generally obtains better image quality; however, it needs matched rawdata sets. This means that physically the same lines need to be measured for each spectrum. In today's CT scanners, this is not the case. The authors propose a new image-based method to combine mismatched rawdata sets for DECT information. The method allows for implementation in a scanner's rawdata precorrection pipeline or may be used in image domain. They compare the ability of the three methods (image-based standard method, proposed method, and rawdata-based standard method) to perform material decomposition and to provide monochromatic images. Thereby they use typical clinical and preclinical scanner arrangements including circular cone-beam CT and spiral CT. The proposed method is found to perform better than the image-based standard method and is inferior to the rawdata-based method. However, the proposed method can be used with the frequent case of mismatched data sets that exclude rawdata-based methods.
Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc
2009-08-01
Dual energy CT (DECT) measures the object of interest using two different x-ray spectra in order to provide energy-selective CT images or in order to get the material decomposition of the object. Today, two decomposition techniques are known. Image-based DECT uses linear combinations of reconstructed images to get an image that contains material-selective DECT information. Rawdata-based DECT correctly treats the available information by passing the rawdata through a decomposition function that uses information from both rawdata sets to create DECT specific (e.g., material-selective) rawdata. Then the image reconstruction yields material-selective images. Rawdata-based image decomposition generally obtains better image quality; however, it needs matched rawdata sets. This means that physically the same lines need to be measured for each spectrum. In today's CT scanners, this is not the case. The authors propose a new image-based method to combine mismatched rawdata sets for DECT information. The method allows for implementation in a scanner's rawdata precorrection pipeline or may be used in image domain. They compare the ability of the three methods (image-based standard method, proposed method, and rawdata-based standard method) to perform material decomposition and to provide monochromatic images. Thereby they use typical clinical and preclinical scanner arrangements including circular cone-beam CT and spiral CT. The proposed method is found to perform better than the image-based standard method and is inferior to the rawdata-based method. However, the proposed method can be used with the frequent case of mismatched data sets that exclude rawdata-based methods. © 2009 American Association of Physicists in Medicine.
Enzyme-Catalyzed Henry Reaction in Choline Chloride-Based Deep Eutectic Solvents.
Tian, Xuemei; Zhang, Suoqin; Zheng, Liangyu
2016-01-01
The enzyme-catalyzed Henry reaction was realized using deep eutectic solvents (DESs) as a reaction medium. The lipase from Aspergillus niger (lipase AS) showed excellent catalytic activity toward the substrates aromatic aldehydes and nitromethane in choline chloride:glycerol at a molar ratio of 1:2. Addition of 30 vol% water to DES further improved the lipase activity and inhibited DES-catalyzed transformation. A final yield of 92.2% for the lipase AS-catalyzed Henry reaction was achieved under optimized reaction conditions in only 4 h. In addition, the lipase AS activity was improved by approximately 3-fold in a DES-water mixture compared with that in pure water, which produced a final yield of only 33.4%. Structural studies with fluorescence spectroscopy showed that the established strong hydrogen bonds between DES and water may be the main driving force that affects the spatial conformation of the enzyme, leading to a change in lipase activity. The methodology was also extended to the aza-Henry reaction, which easily occurred in contrast to that in pure water. The enantioselectivity of both Henry and aza-Henry reactions was not found. However, the results are still remarkable, as we report the first use of DES as a reaction medium in a lipase-catalyzed Henry reaction.
Cicone, A; Liu, J; Zhou, H
2016-04-13
Chemicals released in the air can be extremely dangerous for human beings and the environment. Hyperspectral images can be used to identify chemical plumes, however the task can be extremely challenging. Assuming we know a priori that some chemical plume, with a known frequency spectrum, has been photographed using a hyperspectral sensor, we can use standard techniques such as the so-called matched filter or adaptive cosine estimator, plus a properly chosen threshold value, to identify the position of the chemical plume. However, due to noise and inadequate sensing, the accurate identification of chemical pixels is not easy even in this apparently simple situation. In this paper, we present a post-processing tool that, in a completely adaptive and data-driven fashion, allows us to improve the performance of any classification methods in identifying the boundaries of a plume. This is done using the multidimensional iterative filtering (MIF) algorithm (Cicone et al. 2014 (http://arxiv.org/abs/1411.6051); Cicone & Zhou 2015 (http://arxiv.org/abs/1507.07173)), which is a non-stationary signal decomposition method like the pioneering empirical mode decomposition method (Huang et al. 1998 Proc. R. Soc. Lond. A 454, 903. (doi:10.1098/rspa.1998.0193)). Moreover, based on the MIF technique, we propose also a pre-processing method that allows us to decorrelate and mean-centre a hyperspectral dataset. The cosine similarity measure, which often fails in practice, appears to become a successful and outperforming classifier when equipped with such a pre-processing method. We show some examples of the proposed methods when applied to real-life problems. © 2016 The Author(s).
NASA Astrophysics Data System (ADS)
Kawabe, Yutaka; Yoshikawa, Toshio; Chida, Toshifumi; Tada, Kazuhiro; Kawamoto, Masuki; Fujihara, Takashi; Sassa, Takafumi; Tsutsumi, Naoto
2015-10-01
In order to analyze the spectra of inseparable chemical mixtures, many mathematical methods have been developed to decompose them into the components relevant to species from series of spectral data obtained under different conditions. We formulated a method based on singular value decomposition (SVD) of linear algebra, and applied it to two example systems of organic dyes, being successful in reproducing absorption spectra assignable to cis/trans azocarbazole dyes from the spectral data after photoisomerization and to monomer/dimer of cyanine dyes from those during photodegaradation process. For the example of photoisomerization, polymer films containing the azocarbazole dyes were prepared, which have showed updatable holographic stereogram for real images with high performance. We made continuous monitoring of absorption spectrum after optical excitation and found that their spectral shapes varied slightly after the excitation and during recovery process, of which fact suggested the contribution from a generated photoisomer. Application of the method was successful to identify two spectral components due to trans and cis forms of azocarbazoles. Temporal evolution of their weight factors suggested important roles of long lifetimed cis states in azocarbazole derivatives. We also applied the method to the photodegradation of cyanine dyes doped in DNA-lipid complexes which have shown efficient and durable optical amplification and/or lasing under optical pumping. The same SVD method was successful in the extraction of two spectral components presumably due to monomer and H-type dimer. During the photodegradation process, absorption magnitude gradually decreased due to decomposition of molecules and their decaying rates strongly depended on the spectral components, suggesting that the long persistency of the dyes in DNA-complex related to weak tendency of aggregate formation.
Keszler, Agnes; Diers, Anne R; Ding, Zhen; Hogg, Neil
2017-05-01
Dinitrosyl iron complexes (DNIC) spontaneously form in aqueous solutions of Fe(II), nitric oxide (NO), and various anions. They exist as an equilibrium between diamagnetic, dimeric (bi-DNIC) and paramagnetic, monomeric (mono-DNIC) forms. Thiolate groups (e.g., on glutathione or protein cysteine residues) are the most biologically relevant anions to coordinate to Fe(II). Low molecular weight DNIC have previously been suggested to be important mediators of NO biology in cells, and emerging literature supports their role in the control of iron-dependent cellular processes. Recently, it was shown that DNIC may be one of the most abundant NO-derived products in cells and may serve as intermediates in the cellular formation of S-nitrosothiols. In this work, we examined the stability of low molecular weight DNIC and investigated issues with their detection in the presence of other NO-dependent metabolites such as S-nitrosothiols. By using spectrophotometric, Electron Paramagnetic Resonance, ozone-based chemiluminesence, and HPLC techniques we established that at neutral pH, bi-DNIC remain stable for hours, whereas excess thiol results in decomposition to form nitrite. NO was also detected during the decomposition, but no S-nitrosothiol formation was observed. Importantly, mercury chloride accelerated the degradation of DNIC; thus, the implications of this finding for the diagnostic use of mercury chloride in the detection of S-nitrosothiols were determined in simple and complex biological systems. We conclude S-nitrosothiol levels may have been substantially overestimated in all methods where mercury chloride has been used. Copyright © 2017. Published by Elsevier Inc.
Enstrophy-based proper orthogonal decomposition for reduced-order modeling of flow past a cylinder.
Sengupta, T K; Haider, S I; Parvathi, M K; Pallavi, G
2015-04-01
Here proper orthogonal decomposition (POD) modal decomposition are performed for flow past a circular cylinder at supercritical Reynolds numbers by projecting this onto instability modes. The important task of modeling a cylinder wake by Stuart-Landau (SL) and the Stuart-Landau-Eckhaus (SLE) equation for instability modes is discussed, with the latter shown to be more consistent with multimodal pictures of POD and instability modes. The difficult task of finding the coefficients of the SLE equation is reported by taking a least squares approach for the reduced order model (ROM). The important aspect of the ROM is the choice of initial condition for the developed SLE equations, as these are stiff ordinary differential equations which are very sensitive to the choice of initial conditions. An accurate representation of enstrophy-based POD also reveals the presence of modes which occur in isolation (in comparison to modes that come in pairs) and the traditional approach of treating instability modes by SL or SLE equations does not work directly, which also reveals higher frequency variations. Quantifying effects of this mode by time-averaged Navier-Stokes equation (NSE) fail to show the variation of the phase of these isolated time-varying modes and this is captured here using direct numerical simulation (DNS) data by a multitime scale approach. A reconstructed 3-mode ROM solution and the disturbance vorticity from DNS match globally in the flow. The agreement between 3-mode SLE reconstruction and DNS also proves the consistency of the proposed method and helps explain the physical nature of the ensuing Hopf bifurcation following an instability.
Seasonal variations of MLT tides revealed by a meteor radar chain based on Hough mode decomposition
NASA Astrophysics Data System (ADS)
Yu, Y.; Wan, W.
2016-12-01
Seasonal variations of different tides in the mesosphere and lower thermosphere (MLT) are investigated from wind observations of a four-station meteor radar chain located at middle- and low-latitudes along the 120°E meridian in the Northern Hemisphere on the basis of Hough mode decomposition. Firstly, the observed winds are decomposed into different (diurnal, semidiurnal and terdiurnal) tidal components. Different seasonal patterns are revealed for each component. Pronounced semiannual oscillation (SAO) is presented in the diurnal component. While latitude-depended seasonal variation is found in the semidiurnal and terdiurnal components. At the low/mid- latitude stations, the semiannual/annual oscillation is relatively stronger. Then, Hough mode decomposition is utilized to extract the dominant tidal modes of each decomposed component. It is found that each component is dominated by one of its symmetric tidal modes with strong seasonal dependency. Apparent SAO is observed in the dominant (1, 1) mode; (2, 4) mode is strong in the autumn and winter months (after the Sep. equinox). Based on the extracted results we further propose a technique to map the three-dimensional distribution (latitude × altitude × season) of MLT tidal components from the observations the meteor radar chain located at middle- and low-latitudes along the 120_E meridian in the Northern Hemisphere. The mapped results are finally compared with the corresponding values observed by the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) Doppler Interferometer (TIDI) and modeled from the Global Scale Wave Model (GSWM). Each mapped tidal component agrees well with corresponding TIDI observation in the seasonal variation. Meanwhile, coincidences are found in the seasonal dependency of the diurnal component between the mapped values and the modeled results from GSWM, while difference between them exists in that of the semidiurnal one. Thus, we conclude that the meteor radar chain is
Hydrated electron based decomposition of perfluorooctane sulfonate (PFOS) in the VUV/sulfite system.
Gu, Yurong; Liu, Tongzhou; Wang, Hongjie; Han, Huili; Dong, Wenyi
2017-12-31
As one of the most reactive species, hydrated electron (eaq(-)) is promising for reductive decomposition of recalcitrant organic pollutants, such as perfluorooctane sulfonate (PFOS). In this study, PFOS decomposition using a vacuum ultraviolet (VUV)/sulfite system was systematically investigated in comparison with sole VUV and ultraviolet (UV)/sulfite systems. A fast and nearly complete (97.3%) PFOS decomposition was observed within 4h from its initial concentration of 37.2μM in the VUV/sulfite system. The observed rate constant (kobs) for PFOS decomposition in the studied system was 0.87±0.0060h(-1), which was nearly 7.5 and 2 folds faster than that in sole VUV and UV/sulfite systems, respectively. Compared to previously studied UV/sulfite system, VUV/sulfite system enhanced PFOS decomposition in both weak acidic and alkaline pH conditions. In weak acidic condition (pH6.0), PFOS predominantly decomposed via direct VUV photolysis, whereas in alkaline condition (pH>9.0), PFOS decomposition was mainly induced by eaq(-) generated from both sulfite and VUV photolytic reactions. At a fixed initial solution pH (pH10.0), PFOS decomposition kinetics showed a positive linear dependence with sulfite dosage. The co-presence of humic acid (HA) and NO3(-) obviously suppressed PFOS decomposition, whereas HCO3(-) showed marginal inhibition. A few amount of short chain perfluorocarboxylic acids (PFCAs) were detected in PFOS decomposition process, and a high defluorination efficiency (75.4%) was achieved. These results suggested most fluorine atoms in PFOS molecule ultimately mineralized into fluoride ions, and the mechanisms for PFOS decomposition in the VUV/sulfite system were proposed. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
L'vov, P. E.; Svetukhin, V. V.
2016-07-01
Based on the free energy density functional method, the early stage of decomposition of a onedimensional binary alloy corresponding to the approximation of regular solutions has been simulated. In the simulation, Gaussian composition fluctuations caused by the initial alloy state are taken into account. The calculation is performed using the block approach implying discretization of the extensive solution volume into independent fragments for each of which the decomposition process is calculated, and then a joint analysis of the formed second phase segregations is performed. It was possible to trace all stages of solid solution decomposition: nucleation, growth, and coalescence (initial stage). The time dependences of the main phase distribution characteristics are calculated: the average size and concentration of the second phase particles, their size distribution function, and the nucleation rate of the second phase particles (clusters). Cluster trajectories in the size-composition space are constructed for the cases of growth and dissolution.
NASA Astrophysics Data System (ADS)
Wang, Yingying; Zhang, Dongju; Liu, Peng; Liu, Chengbu
2016-08-01
Existing theoretical results for formic acid (HCOOH) decomposition on Pt(1 1 1) cannot rationalize the easy CO poisoning of the catalysts in the gas phase. The present work reexamined HCOOH decomposition on Pt(1 1 1) by considering the effect of the initial adsorption structure of the reactant on the reactivity. Our calculations present a new adsorption configuration of HCOOH on Pt(1 1 1), from which the formation of CO is found to be competing with the formation of CO2. The newly proposed mechanism improves our understanding for the mechanism of HCOOH decomposition catalyzed by Pt-based catalysts.
Embedding empirical mode decomposition within an FPGA-based design: challenges and progress
NASA Astrophysics Data System (ADS)
Jones, Jonathan D.; Pei, Jin-Song; Wright, Joseph P.
2011-04-01
This paper presents further advancements made in an ongoing project following a series of presentations made at the same SPIE conference in the past. Compared with traditional microprocessor-based systems, rapidly advancing field-programmable gate array (FPGA) technology offers a more powerful, efficient and flexible hardware platform. An FPGA-based design is developed to classify three types of nonlinearities (including linear, hardening and softening) of a single-degree-of-freedom (SDOF) system subjected to free vibration. This significantly advances the team's previous work on using FPGAs for wireless structural health monitoring. The classification is achieved by embedding two important algorithms - empirical mode decomposition (EMD) and backbone curve analysis. A series of systematic efforts is made to embed EMD, which involves cubic spline fitting, in an FPGA-based hardware design. Throughout the process, we take advantage of concurrent operation and strive for a trade-off between computational efficiency and resource utilization. We have started to pursue our work in the context of FPGA-based computation. In particular, handling fixed-point precision is framed under data-path optimization. Our approach for data-path optimization is necessarily manual and thus may not guarantee an optimal design. Nonetheless, our study could provide a baseline case for future work using analytical data-path optimization for this and numerous other powerful algorithms for wireless structural health monitoring.
Zhu, Huazheng; He, Zhongshi; Jia, Yuanyuan
2016-03-01
Multiple sequence alignment (MSA) is a fundamental and key step for implementing other tasks in bioinformatics, such as phylogenetic analyses, identification of conserved motifs and domains, structure prediction, etc. Despite the fact that there are many methods to implement MSA, biologically perfect alignment approaches are not found hitherto. This paper proposes a novel idea to perform MSA, where MSA is treated as a multiobjective optimization problem. A famous multiobjective evolutionary algorithm framework based on decomposition is applied for solving MSA, named MOMSA. In the MOMSA algorithm, we develop a new population initialization method and a novel mutation operator. We compare the performance of MOMSA with several alignment methods based on evolutionary algorithms, including VDGA, GAPAM, and IMSA, and also with state-of-the-art progressive alignment approaches, such as MSAprobs, Probalign, MAFFT, Procons, Clustal omega, T-Coffee, Kalign2, MUSCLE, FSA, Dialign, PRANK, and CLUSTALW. These alignment algorithms are tested on benchmark datasets BAliBASE 2.0 and BAliBASE 3.0. Experimental results show that MOMSA can obtain the significantly better alignments than VDGA, GAPAM on the most of test cases by statistical analyses, produce better alignments than IMSA in terms of TC scores, and also indicate that MOMSA is comparable with the leading progressive alignment approaches in terms of quality of alignments.
NASA Astrophysics Data System (ADS)
Incerti, Guido; Bonanomi, Giuliano; Sarker, Tushar Chandra; Giannino, Francesco; Cartenì, Fabrizio; Peressotti, Alessandro; Spaccini, Riccardo; Piccolo, Alessandro; Mazzoleni, Stefano
2017-04-01
Modelling organic matter decomposition is fundamental to predict biogeochemical cycling in terrestrial ecosystems. Current models use C/N or Lignin/N ratios to describe susceptibility to decomposition, or implement separate C pools decaying with different rates, disregarding biomolecular transformations and interactions and their effect on decomposition dynamics. We present a new process-based model of decomposition that includes a description of biomolecular dynamics obtained by 13C-CPMAS NMR spectroscopy. Baseline decay rates for relevant molecular classes and intermolecular protection were calibrated by best fitting of experimental data from leaves of 20 plant species decomposing for 180 days in controlled optimal conditions. The model was validated against field data from leaves of 32 plant species decomposing for 1-year at four sites in Mediterranean ecosystems. Our innovative approach accurately predicted decomposition of a wide range of litters across different climates. Simulations correctly reproduced mass loss data and variations of selected molecular classes both in controlled conditions and in the field, across different plant molecular compositions and environmental conditions. Prediction accuracy emerged from the species-specific partitioning of molecular types and from the representation of intermolecular interactions. The ongoing model implementation and calibration are oriented at representing organic matter dynamics in soil, including processes of interaction between mineral and organic soil fractions as a function of soil texture, physical aggregation of soil organic particles, and physical protection of soil organic matter as a function of aggregate size and abundance. Prospectively, our model shall satisfactorily reproduce C sequestration as resulting from experimental data of soil amended with a range of organic materials with different biomolecular quality, ranging from biochar to crop residues. Further application is also planned based on
Ji, Fanghua; Peng, Hui; Zhang, Xiaoting; Lu, Wenhua; Liu, Shubin; Jiang, Huanfeng; Liu, Bo; Yin, Biaolin
2015-02-20
Base-mediated decomposition of amide-substituted furfuryl tosylhydrazones afforded practical access to novel multifunctionalized enynyl-ketoamides. In addition, furfuryl tosylhydrazones with stable furan rings underwent an interesting tosyl-group migration to form sulfones, which have potential synthetic applications. Some of the obtained enynyl-ketoamides demonstrated good cytotoxicities against human tumor cell lines.
Target detection for low cost uncooled MWIR cameras based on empirical mode decomposition
NASA Astrophysics Data System (ADS)
Piñeiro-Ave, José; Blanco-Velasco, Manuel; Cruz-Roldán, Fernando; Artés-Rodríguez, Antonio
2014-03-01
In this work, a novel method for detecting low intensity fast moving objects with low cost Medium Wavelength Infrared (MWIR) cameras is proposed. The method is based on background subtraction in a video sequence obtained with a low density Focal Plane Array (FPA) of the newly available uncooled lead selenide (PbSe) detectors. Thermal instability along with the lack of specific electronics and mechanical devices for canceling the effect of distortion make background image identification very difficult. As a result, the identification of targets is performed in low signal to noise ratio (SNR) conditions, which may considerably restrict the sensitivity of the detection algorithm. These problems are addressed in this work by means of a new technique based on the empirical mode decomposition, which accomplishes drift estimation and target detection. Given that background estimation is the most important stage for detecting, a previous denoising step enabling a better drift estimation is designed. Comparisons are conducted against a denoising technique based on the wavelet transform and also with traditional drift estimation methods such as Kalman filtering and running average. The results reported by the simulations show that the proposed scheme has superior performance.
Bathymetric depth sounder with novel echo signal analysis based on exponential decomposition
NASA Astrophysics Data System (ADS)
Ullrich, Andreas; Pfennigbauer, Martin; Schwarz, Roland
2017-05-01
We present a laser rangefinder specifically designed for bathymetric surveying tasks. The compact and lightweight instrument is capable of measuring through the water surface, ideally suited for generating profiles of waterbodies when operated from a UAV. The topo-bathymetric LiDAR sensor comprises a tilt compensation, an IMU/GNSS unit with antenna, a control unit, and supports triggering of external digital cameras. The laser range finder sends out laser pulses at a rate of 4 kHz. The echo signal for each laser pulse is digitized and recorded for the entire range gate of 50 m. This means that predetection averaging of the waveforms can be performed in post processing, increasing the depth performance. The averaging rate can be chosen after the flight on basis of measurement conditions. The waveforms are processed by a full waveform processing algorithm based on exponential decomposition which uses segments of an exponential function as base functions to model the backscatter cross-section of the target objects. Water surface, water column, and ground targets are modeled using a set of base functions of which an optimization selects the most suitable combination to fit the echo signal. This leads to high accuracy of the points and to automatic target classification.
Hydrogen peroxide catalytic decomposition
NASA Technical Reports Server (NTRS)
Parrish, Clyde F. (Inventor)
2010-01-01
Nitric oxide in a gaseous stream is converted to nitrogen dioxide using oxidizing species generated through the use of concentrated hydrogen peroxide fed as a monopropellant into a catalyzed thruster assembly. The hydrogen peroxide is preferably stored at stable concentration levels, i.e., approximately 50%-70% by volume, and may be increased in concentration in a continuous process preceding decomposition in the thruster assembly. The exhaust of the thruster assembly, rich in hydroxyl and/or hydroperoxy radicals, may be fed into a stream containing oxidizable components, such as nitric oxide, to facilitate their oxidation.
NASA Astrophysics Data System (ADS)
Wang, Haijun; Xu, Feiyun; Zhao, Jun'ai; Jia, Minping; Hu, Jianzhong; Huang, Peng
2013-11-01
Nonnegative Tucker3 decomposition(NTD) has attracted lots of attentions for its good performance in 3D data array analysis. However, further research is still necessary to solve the problems of overfitting and slow convergence under the anharmonic vibration circumstance occurred in the field of mechanical fault diagnosis. To decompose a large-scale tensor and extract available bispectrum feature, a method of conjugating Choi-Williams kernel function with Gauss-Newton Cartesian product based on nonnegative Tucker3 decomposition(NTD_EDF) is investigated. The complexity of the proposed method is reduced from o( n N lg n) in 3D spaces to o( R 1 R 2 nlg n) in 1D vectors due to its low rank form of the Tucker-product convolution. Meanwhile, a simultaneously updating algorithm is given to overcome the overfitting, slow convergence and low efficiency existing in the conventional one-by-one updating algorithm. Furthermore, the technique of spectral phase analysis for quadratic coupling estimation is used to explain the feature spectrum extracted from the gearbox fault data by the proposed method in detail. The simulated and experimental results show that the sparser and more inerratic feature distribution of basis images can be obtained with core tensor by the NTD_EDF method compared with the one by the other methods in bispectrum feature extraction, and a legible fault expression can also be performed by power spectral density(PSD) function. Besides, the deviations of successive relative error(DSRE) of NTD_EDF achieves 81.66 dB against 15.17 dB by beta-divergences based on NTD(NTD_Beta) and the time-cost of NTD_EDF is only 129.3 s, which is far less than 1 747.9 s by hierarchical alternative least square based on NTD (NTD_HALS). The NTD_EDF method proposed not only avoids the data overfitting and improves the computation efficiency but also can be used to extract more inerratic and sparser bispectrum features of the gearbox fault.
Lewis base activation of Lewis acids: development of a Lewis base catalyzed selenolactonization.
Denmark, Scott E; Collins, William R
2007-09-13
The concept of Lewis base activation of Lewis acids has been applied to the selenolactonization reaction. Through the use of substoichiometric amounts of Lewis bases with "soft" donor atoms (S, Se, P) significant rate enhancements over the background reaction are seen. Preliminary mechanistic investigations have revealed the resting state of the catalyst as well as the significance of a weak Brønsted acid promoter.
Michida, Makoto; Mukaiyama, Teruaki
2008-09-01
Lewis base-catalyzed 1,3-dithiane addition to electrophiles such as carbonyl compounds and N-substituted aldimines with 2-trimethylsilyl-1,3-dithiane (TMS-dithiane) is described. By the activation of the carbon-silicon bond in the presence of a Lewis base catalyst such as tetrabutylammonium phenoxide (PhONnBu(4)), a 1,3-dithiane addition reaction proceeded smoothly to afford the corresponding adducts in good to high yields under mild conditions. This synthesis is also applied to the reactions of ketones having alpha-protons, and of N-substituted aldimines.
Using the base-of-the-pyramid perspective to catalyze interdependence-based collaborations.
London, Ted; Anupindi, Ravi
2012-07-31
Improving food security and nutrition in the developing world remains among society's most intractable challenges and continues despite a wide variety of investments. Both donor- and enterprise-led initiatives, for example, have explored including smallholder farmers in their value chains. However, these efforts have had only modest success, partly because the private and development sectors prefer to maintain their independence. Research from the base-of-the-pyramid domain offers new insights into how collaborative interdependence between sectors can enhance the connection between profits and the alleviation of poverty. In this article, we identify the strengths and weaknesses of donor-led and enterprise-led value chain initiatives. We then explore how insights from the base-of-the-pyramid domain yield a set of interdependence-based collaboration strategies that can achieve more sustainable and scalable outcomes.
Using the base-of-the-pyramid perspective to catalyze interdependence-based collaborations
London, Ted; Anupindi, Ravi
2012-01-01
Improving food security and nutrition in the developing world remains among society's most intractable challenges and continues despite a wide variety of investments. Both donor- and enterprise-led initiatives, for example, have explored including smallholder farmers in their value chains. However, these efforts have had only modest success, partly because the private and development sectors prefer to maintain their independence. Research from the base-of-the-pyramid domain offers new insights into how collaborative interdependence between sectors can enhance the connection between profits and the alleviation of poverty. In this article, we identify the strengths and weaknesses of donor-led and enterprise-led value chain initiatives. We then explore how insights from the base-of-the-pyramid domain yield a set of interdependence-based collaboration strategies that can achieve more sustainable and scalable outcomes. PMID:21482752
A Fusion Breeder Reactor Based on a Catalyzed D-D Spherical Torus.
1986-08-08
cooling and fissile breeding. The need for tritium breeding is eliminated by the use of’ a catalyzed 0-0 fuel cycle. Analysis of this novel reactor...in heavy water which flows through the first wall and blanket providing both cooling and fissile breeding. The need I for tritium breeding is...studies in that: (1) a deuterium fuel cycle is used to eliminate the : need to breed tritium ; (2) a compact tokamak (spherical torus) is used as a
He, Jingjing; Zhou, Yibin; Guan, Xuefei; Zhang, Wei; Zhang, Weifang; Liu, Yongming
2016-01-01
Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided. PMID:27537889
Region quad-tree decomposition based edge detection for medical images.
Dua, Sumeet; Kandiraju, Naveen; Chowriappa, Pradeep
2010-05-28
Edge detection in medical images has generated significant interest in the medical informatics community, especially in recent years. With the advent of imaging technology in biomedical and clinical domains, the growth in medical digital images has exceeded our capacity to analyze and store them for efficient representation and retrieval, especially for data mining applications. Medical decision support applications frequently demand the ability to identify and locate sharp discontinuities in an image for feature extraction and interpretation of image content, which can then be exploited for decision support analysis. However, due to the inherent high dimensional nature of the image content and the presence of ill-defined edges, edge detection using classical procedures is difficult, if not impossible, for sensitive and specific medical informatics-based discovery. In this paper, we propose a new edge detection technique based on the regional recursive hierarchical decomposition using quadtree and post-filtration of edges using a finite difference operator. We show that in medical images of common origin, focal and/or penumbral blurred edges can be characterized by an estimable intensity gradient. This gradient can further be used for dismissing false alarms. A detailed validation and comparison with related works on diabetic retinopathy images and CT scan images show that the proposed approach is efficient and accurate.
Research of singular value decomposition based on slip matrix for rolling bearing fault diagnosis
NASA Astrophysics Data System (ADS)
Cong, Feiyun; Zhong, Wei; Tong, Shuiguang; Tang, Ning; Chen, Jin
2015-05-01
Rolling element bearings are at the heart of most rotating machines and they bear the function of connectivity between the rotor and stator. It is important to distinguish the incipient fault before the bearing step into serious failure. The Slip Matrix (SM) construction method based on Singular Value Decomposition (SVD) is proposed in this paper. The SM based fault feature extraction and impulses intelligent detection methods are introduced as the key steps for rolling bearing fault diagnosis. The numerical simulation of rolling bearing fault signal is adopted which shows that the proposed method is good at fault impulses detection in strong background noise environment. The rolling element bearing accelerated life test is performed for the acquisition of experimental data of rolling bearing fault. With the rolling bearing running from normal state to failure, the initial fault signal part can be picked out from the whole life vibration data of the rolling bearing. The vibration signal is close to the nature fault signal which is acquired from a rolling bearing applied in industrial field. The analysis result shows that the proposed method has an excellent performance in rolling bearing fault detection.
Electrocardiogram signal denoising based on empirical mode decomposition technique: an overview
NASA Astrophysics Data System (ADS)
Han, G.; Lin, B.; Xu, Z.
2017-03-01
Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects whether the heart is functioning normally or abnormally. ECG signal is susceptible to various kinds of noises such as high/low frequency noises, powerline interference and baseline wander. Hence, the removal of noises from ECG signal becomes a vital link in the ECG signal processing and plays a significant role in the detection and diagnosis of heart diseases. The review will describe the recent developments of ECG signal denoising based on Empirical Mode Decomposition (EMD) technique including high frequency noise removal, powerline interference separation, baseline wander correction, the combining of EMD and Other Methods, EEMD technique. EMD technique is a quite potential and prospective but not perfect method in the application of processing nonlinear and non-stationary signal like ECG signal. The EMD combined with other algorithms is a good solution to improve the performance of noise cancellation. The pros and cons of EMD technique in ECG signal denoising are discussed in detail. Finally, the future work and challenges in ECG signal denoising based on EMD technique are clarified.
NASA Astrophysics Data System (ADS)
Gu, Yue; Han, Junxia; Liang, Zhenhu; Yan, Jiaqing; Li, Zheng; Li, Xiaoli
2016-01-01
Functional near-infrared spectroscopy (fNIRS) is a promising technique for monitoring brain activity. However, it is sensitive to motion artifacts. Many methods have been developed for motion correction, such as spline interpolation, wavelet filtering, and kurtosis-based wavelet filtering. We propose a motion correction method based on empirical mode decomposition (EMD), which is applied to segments of data identified as having motion artifacts. The EMD method is adaptive, data-driven, and well suited for nonstationary data. To test the performance of the proposed EMD method and to compare it with other motion correction methods, we used simulated hemodynamic responses added to real resting-state fNIRS data. The EMD method reduced mean squared error in 79% of channels and increased signal-to-noise ratio in 78% of channels. Moreover, it produced the highest Pearson's correlation coefficient between the recovered signal and the original signal, significantly better than the comparison methods (p<0.01, paired t-test). These results indicate that the proposed EMD method is a first choice method for motion artifact correction in fNIRS.
Wen, Qiaonong; Wan, Suiren
2013-01-01
Ultrasound image deconvolution involves noise reduction and image feature enhancement, denoising need equivalent the low-pass filtering, image feature enhancement is to strengthen the high-frequency parts, these two requirements are often combined together. It is a contradictory requirement that we must be reasonable balance between these two basic requirements. Image deconvolution method of partial differential equation model is the method based on diffusion theory, and sparse decomposition deconvolution is image representation-based method. The mechanisms of these two methods are not the same, effect of these two methods own characteristics. In contourlet transform domain, we combine the strengths of the two deconvolution method together by image fusion, and introduce the entropy of local orientation energy ratio into fusion decision-making, make a different treatment according to the actual situation on the low-frequency part of the coefficients and the high-frequency part of the coefficient. As deconvolution process is inevitably blurred image edge information, we fusion the edge gray-scale image information to the deconvolution results in order to compensate the missing edge information. Experiments show that our method is better than the effect separate of using deconvolution method, and restore part of the image edge information.
Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition
2013-01-01
Background DNA microarrays are used for discovery of genes expressed differentially between various biological conditions. In microarray experiments the number of analyzed samples is often much lower than the number of genes (probe sets) which leads to many false discoveries. Multiple testing correction methods control the number of false discoveries but decrease the sensitivity of discovering differentially expressed genes. Concerning this problem, filtering methods for improving the power of detection of differentially expressed genes were proposed in earlier papers. These techniques are two-step procedures, where in the first step some pool of non-informative genes is removed and in the second step only the pool of the retained genes is used for searching for differentially expressed genes. Results A very important parameter to choose is the proportion between the sizes of the pools of removed and retained genes. A new method, which we propose, allow to determine close to optimal threshold values for sample means and sample variances for gene filtering. The method is adaptive and based on the decomposition of the histogram of gene expression means or variances into mixture of Gaussian components. Conclusions By performing analyses of several publicly available datasets and simulated datasets we demonstrate that our adaptive method increases sensitivity of finding differentially expressed genes compared to previous methods of filtering microarray data based on using fixed threshold values. PMID:23510016
Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.
Park, Chulhee; Kang, Moon Gi
2016-05-18
A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.
He, Jingjing; Zhou, Yibin; Guan, Xuefei; Zhang, Wei; Zhang, Weifang; Liu, Yongming
2016-08-16
Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.
Enhancement of lung sounds based on empirical mode decomposition and Fourier transform algorithm.
Mondal, Ashok; Banerjee, Poulami; Somkuwar, Ajay
2017-02-01
There is always heart sound (HS) signal interfering during the recording of lung sound (LS) signals. This obscures the features of LS signals and creates confusion on pathological states, if any, of the lungs. In this work, a new method is proposed for reduction of heart sound interference which is based on empirical mode decomposition (EMD) technique and prediction algorithm. In this approach, first the mixed signal is split into several components in terms of intrinsic mode functions (IMFs). Thereafter, HS-included segments are localized and removed from them. The missing values of the gap thus produced, is predicted by a new Fast Fourier Transform (FFT) based prediction algorithm and the time domain LS signal is reconstructed by taking an inverse FFT of the estimated missing values. The experiments have been conducted on simulated and recorded HS corrupted LS signals at three different flow rates and various SNR levels. The performance of the proposed method is evaluated by qualitative and quantitative analysis of the results. It is found that the proposed method is superior to the baseline method in terms of quantitative and qualitative measurement. The developed method gives better results compared to baseline method for different SNR levels. Our method gives cross correlation index (CCI) of 0.9488, signal to deviation ratio (SDR) of 9.8262, and normalized maximum amplitude error (NMAE) of 26.94 for 0 dB SNR value. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition
Park, Chulhee; Kang, Moon Gi
2016-01-01
A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors. PMID:27213381
NASA Astrophysics Data System (ADS)
Minei, A. J.; Cooke, S. A.
2013-06-01
A singular value decomposition (SVD) signal processing method is newly applied to molecular free induction decays (FIDs) obtained using a time domain, broadband rotational spectrometer. It is demonstrated that for the strongest spectral transitions the SVD method can determine transition frequencies with a precision matching that of the fast Fourier transform method. Furthermore, the SVD-based analysis produces information concerning transition phase, amplitude, damping, and frequency for the strongest molecular signals. These parameters are shown as useful in regards to time-domain signal filtering. The computational expense of the SVD method is high and therefore this approach has the disadvantage that with our present computers the full molecular FID must be considerably truncated. The effects of FID truncation on the determined transition frequencies have been examined. Conversely, this truncation method illustrates that broadband spectra may be recovered from fragments as small as 1 % of the complete FID. The success of the SVD-based method is further examined in regards to weak signal detection, and frequency dependent detection. The pure rotational spectrum of 1H,1H,2H-perfluorocyclobutane is used for illustrative purposes in this study.
A classification algorithm based on Cloude decomposition model for fully polarimetric SAR image
NASA Astrophysics Data System (ADS)
Xiang, Hongmao; Liu, Shanwei; Zhuang, Ziqi; Zhang, Naixin
2016-11-01
Remote sensing is an important technology for monitoring coastal zone, but it is difficult to get effective optical data in cloudy or rainy weather. SAR is an important data source for monitoring the coastal zone because it cannot be restricted in all-weather. Fully polarimetric SAR data is more abundant than single polarization and multi-polarization SAR data. The experiment selected the fully polarimetric SAR image of Radarsat-2, which covered the Yellow River Estuary. In view of the features of the study area, we carried out the H/ α unsupervised classification, the H/ α -Wishart unsupervised classification and the H/ α -Wishart unsupervised classification based on the results of Cloude decomposition. A new classification method is proposed which used the Wishart supervised classification based on the result of H/ α -Wishart unsupervised classification. The experimental results showed that the new method effectively overcome the shortcoming of unsupervised classification and improved the classification accuracy significantly. It was also shown that the classification result of SAR image had the similar precision with that of Landsat-7 image by the same classification method, SAR image had a better precision of water classification due to its sensitivity for water, and Landsat-7 image had a better precision of vegetation types.
Assessment and Improvement of GOCE based Global Geopotential Models Using Wavelet Decomposition
NASA Astrophysics Data System (ADS)
Erol, Serdar; Erol, Bihter; Serkan Isik, Mustafa
2016-07-01
The contribution of recent Earth gravity field satellite missions, specifically GOCE mission, leads significant improvement in quality of gravity field models in both accuracy and resolution manners. However the performance and quality of each released model vary not only depending on the spatial location of the Earth but also the different bands of the spectral expansion. Therefore the assessment of the global model performances with validations using in situ-data in varying territories on the Earth is essential for clarifying their exact performances in local. Beside of this, their spectral evaluation and quality assessment of the signal in each part of the spherical harmonic expansion spectrum is essential to have a clear decision for the commission error content of the model and determining its optimal degree, revealed the best results, as well. The later analyses provide also a perspective and comparison on the global behavior of the models and opportunity to report the sequential improvement of the models depending on the mission developments and hence the contribution of the new data of missions. In this study a review on spectral assessment results of the recently released GOCE based global geopotential models DIR-R5, TIM-R5 with the enhancement using EGM2008, as reference model, in Turkey, versus the terrestrial data is provided. Beside of reporting the GOCE mission contribution to the models in Turkish territory, the possible improvement in the spectral quality of these models, via decomposition that are highly contaminated by noise, is purposed. In the analyses the motivation is on achieving an optimal amount of improvement that rely on conserving the useful component of the GOCE signal as much as possible, while fusing the filtered GOCE based models with EGM2008 in the appropriate spectral bands. The investigation also contain the assessment of the coherence and the correlation between the Earth gravity field parameters (free-air gravity anomalies and
Liao, Chia-Chi; Lo, Yu-Lung
2013-07-15
A hybrid model comprising the differential Mueller matrix formalism and the Mueller matrix decomposition method is proposed for extracting the linear birefringence (LB), linear dichroism (LD), circular birefringence (CB), circular dichroism (CD), and depolarization properties (Dep) of turbid optical samples. In contrast to the differential-based Mueller matrix method, the proposed hybrid model provides full-range measurements of all the anisotropic properties of the optical sample. Furthermore, compared to the decomposition-based Mueller matrix method, the proposed model is insensitive to the multiplication order of the constituent basis matrices. The validity of the proposed method is confirmed by extracting the anisotropic properties of a compound chitosan-glucose-microsphere sample with LB/CB/Dep properties and two ferrofluidic samples with CB/CD/Dep and LB/LD/Dep properties, respectively. It is shown that the proposed hybrid model not only yields full-range measurements of all the anisotropic parameters, but is also more accurate and more stable than the decomposition method. Moreover, compared to the decomposition method, the proposed model more accurately reflects the dependency of the phase retardation angle and linear dichroism angle on the direction of the external magnetic field for ferrofluidic samples. Overall, the results presented in this study confirm that the proposed model has significant potential for extracting the optical parameters of real-world samples characterized by either single or multiple anisotropic properties.
Benchmarking of a T-wave alternans detection method based on empirical mode decomposition.
Blanco-Velasco, Manuel; Goya-Esteban, Rebeca; Cruz-Roldán, Fernando; García-Alberola, Arcadi; Rojo-Álvarez, José Luis
2017-07-01
T-wave alternans (TWA) is a fluctuation of the ST-T complex occurring on an every-other-beat basis of the surface electrocardiogram (ECG). It has been shown to be an informative risk stratifier for sudden cardiac death, though the lack of gold standard to benchmark detection methods has promoted the use of synthetic signals. This work proposes a novel signal model to study the performance of a TWA detection. Additionally, the methodological validation of a denoising technique based on empirical mode decomposition (EMD), which is used here along with the spectral method, is also tackled. The proposed test bed system is based on the following guidelines: (1) use of open source databases to enable experimental replication; (2) use of real ECG signals and physiological noise; (3) inclusion of randomized TWA episodes. Both sensitivity (Se) and specificity (Sp) are separately analyzed. Also a nonparametric hypothesis test, based on Bootstrap resampling, is used to determine whether the presence of the EMD block actually improves the performance. The results show an outstanding specificity when the EMD block is used, even in very noisy conditions (0.96 compared to 0.72 for SNR = 8 dB), being always superior than that of the conventional SM alone. Regarding the sensitivity, using the EMD method also outperforms in noisy conditions (0.57 compared to 0.46 for SNR=8 dB), while it decreases in noiseless conditions. The proposed test setting designed to analyze the performance guarantees that the actual physiological variability of the cardiac system is reproduced. The use of the EMD-based block in noisy environment enables the identification of most patients with fatal arrhythmias. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Zhou, Nengjie; Lu, Zhenyu; Wu, Qin; Zhang, Yingkai
2014-06-01
We examine interatomic interactions for rare gas dimers using the density-based energy decomposition analysis (DEDA) in conjunction with computational results from CCSD(T) at the complete basis set (CBS) limit. The unique DEDA capability of separating frozen density interactions from density relaxation contributions is employed to yield clean interaction components, and the results are found to be consistent with the typical physical picture that density relaxations play a very minimal role in rare gas interactions. Equipped with each interaction component as reference, we develop a new three-term molecular mechanical force field to describe rare gas dimers: a smeared charge multipole model for electrostatics with charge penetration effects, a B3LYP-D3 dispersion term for asymptotically correct long-range attractions that is screened at short-range, and a Born-Mayer exponential function for the repulsion. The resulted force field not only reproduces rare gas interaction energies calculated at the CCSD(T)/CBS level, but also yields each interaction component (electrostatic or van der Waals) which agrees very well with its corresponding reference value.
NASA Astrophysics Data System (ADS)
He, Zhi; Liu, Lin
2016-11-01
Empirical mode decomposition (EMD) and its variants have recently been applied for hyperspectral image (HSI) classification due to their ability to extract useful features from the original HSI. However, it remains a challenging task to effectively exploit the spectral-spatial information by the traditional vector or image-based methods. In this paper, a three-dimensional (3D) extension of EMD (3D-EMD) is proposed to naturally treat the HSI as a cube and decompose the HSI into varying oscillations (i.e. 3D intrinsic mode functions (3D-IMFs)). To achieve fast 3D-EMD implementation, 3D Delaunay triangulation (3D-DT) is utilized to determine the distances of extrema, while separable filters are adopted to generate the envelopes. Taking the extracted 3D-IMFs as features of different tasks, robust multitask learning (RMTL) is further proposed for HSI classification. In RMTL, pairs of low-rank and sparse structures are formulated by trace-norm and l1,2 -norm to capture task relatedness and specificity, respectively. Moreover, the optimization problems of RMTL can be efficiently solved by the inexact augmented Lagrangian method (IALM). Compared with several state-of-the-art feature extraction and classification methods, the experimental results conducted on three benchmark data sets demonstrate the superiority of the proposed methods.
Automatic decomposition of a complex hologram based on the virtual diffraction plane framework
NASA Astrophysics Data System (ADS)
Jiao, A. S. M.; Tsang, P. W. M.; Poon, T.-C.; Liu, J.-P.; Lee, C.-C.; Lam, Y. K.
2014-07-01
Holography is a technique for capturing the hologram of a three-dimensional scene. In many applications, it is often pertinent to retain specific items of interest in the hologram, rather than retaining the full information, which may cause distraction in the analytical process that follows. For a real optical image that is captured with a camera or scanner, this process can be realized by applying image segmentation algorithms to decompose an image into its constituent entities. However, because it is different from an optical image, classic image segmentation methods cannot be applied directly to a hologram, as each pixel in the hologram carries holistic, rather than local, information of the object scene. In this paper, we propose a method to perform automatic decomposition of a complex hologram based on a recently proposed technique called the virtual diffraction plane (VDP) framework. Briefly, a complex hologram is back-propagated to a hypothetical plane known as the VDP. Next, the image on the VDP is automatically decomposed, through the use of the segmentation on the magnitude of the VDP image, into multiple sub-VDP images, each representing the diffracted waves of an isolated entity in the scene. Finally, each sub-VDP image is reverted back to a hologram. As such, a complex hologram can be decomposed into a plurality of subholograms, each representing a discrete object in the scene. We have demonstrated the successful performance of our proposed method by decomposing a complex hologram that is captured through the optical scanning holography (OSH) technique.
Bao, Fei; Li, Chen; Wang, Xinlong; Wang, Qingfu; Du, Shuanping
2010-07-01
Classification for ship-radiated underwater sound is one of the most important and challenging subjects in underwater acoustical signal processing. An approach to ship classification is proposed in this work based on analysis of ship-radiated acoustical noise in subspaces of intrinsic mode functions attained via the ensemble empirical mode decomposition. It is shown that detection and acquisition of stable and reliable nonlinear features become practically feasible by nonlinear analysis of the time series of individual decomposed components, each of which is simple enough and well represents an oscillatory mode of ship dynamics. Surrogate and nonlinear predictability analysis are conducted to probe and measure the nonlinearity and regularity. The results of both methods, which verify each other, substantiate that ship-radiated noises contain components with deterministic nonlinear features well serving for efficient classification of ships. The approach perhaps opens an alternative avenue in the direction toward object classification and identification. It may also import a new view of signals as complex as ship-radiated sound.
Proper Orthogonal Decomposition methods for particle-based transport calculations in plasmas
NASA Astrophysics Data System (ADS)
Del-Castillo-Negrete, Diego; Spong, D.; Hirshman, S.
2009-05-01
The Proper Orthogonal Decomposition (POD) is a powerful technique to analyze large data sets by projecting the data into an optimal set of low-order modes that capture the main features of the data. POD methods have been widely used in image and signal processing and also in the study of coherent structures in neutral fluids. However, the use of these techniques in plasma physics is a relatively new area of research. Here we discuss recent novel applications of POD methods to particle-based transport calculations in plasmas. We show that POD techniques provide an efficient method to filter noise in the reconstruction of the particle distribution function. As a specific application we consider Monte Carlo simulations of plasma collisional relaxation and guiding-center transport in magnetically confined plasma in toroidal geometry [1]. We also discuss recent results on the application of POD methods to PIC-codes in the context of the Vlasov-Poisson system, and the use of POD methods in projective integration. In particular, we show how POD modes can be used as effective macroscopic variables to accelerate Monte-Carlo calculations. [1] D. del-Castillo-Negrete, et al. Phys. of Plasmas 15, 092308 (2008).
Singular value decomposition-based 2D image reconstruction for computed tomography.
Liu, Rui; He, Lu; Luo, Yan; Yu, Hengyong
2017-01-01
Singular value decomposition (SVD)-based 2D image reconstruction methods are developed and evaluated for a broad class of inverse problems for which there are no analytical solutions. The proposed methods are fast and accurate for reconstructing images in a non-iterative fashion. The multi-resolution strategy is adopted to reduce the size of the system matrix to reconstruct large images using limited memory capacity. A modified high-contrast Shepp-Logan phantom, a low-contrast FORBILD head phantom, and a physical phantom are employed to evaluate the proposed methods with different system configurations. The results show that the SVD methods can accurately reconstruct images from standard scan and interior scan projections and that they outperform other benchmark methods. The general SVD method outperforms the other SVD methods. The truncated SVD and Tikhonov regularized SVD methods accurately reconstruct a region-of-interest (ROI) from an internal scan with a known sub-region inside the ROI. Furthermore, the SVD methods are much faster and more flexible than the benchmark algorithms, especially in the ROI reconstructions in our experiments.
Hallander, Jon; Waldmann, Patrik; Wang, Chunkao; Sillanpää, Mikko J
2010-06-01
It is widely recognized that the mixed linear model is an important tool for parameter estimation in the analysis of complex pedigrees, which includes both pedigree and genomic information, and where mutually dependent genetic factors are often assumed to follow multivariate normal distributions of high dimension. We have developed a Bayesian statistical method based on the decomposition of the multivariate normal prior distribution into products of conditional univariate distributions. This procedure permits computationally demanding genetic evaluations of complex pedigrees, within the user-friendly computer package WinBUGS. To demonstrate and evaluate the flexibility of the method, we analyzed two example pedigrees: a large noninbred pedigree of Scots pine (Pinus sylvestris L.) that includes additive and dominance polygenic relationships and a simulated pedigree where genomic relationships have been calculated on the basis of a dense marker map. The analysis showed that our method was fast and provided accurate estimates and that it should therefore be a helpful tool for estimating genetic parameters of complex pedigrees quickly and reliably.
Multidimensional Compressed Sensing MRI Using Tensor Decomposition-Based Sparsifying Transform
Yu, Yeyang; Jin, Jin; Liu, Feng; Crozier, Stuart
2014-01-01
Compressed Sensing (CS) has been applied in dynamic Magnetic Resonance Imaging (MRI) to accelerate the data acquisition without noticeably degrading the spatial-temporal resolution. A suitable sparsity basis is one of the key components to successful CS applications. Conventionally, a multidimensional dataset in dynamic MRI is treated as a series of two-dimensional matrices, and then various matrix/vector transforms are used to explore the image sparsity. Traditional methods typically sparsify the spatial and temporal information independently. In this work, we propose a novel concept of tensor sparsity for the application of CS in dynamic MRI, and present the Higher-order Singular Value Decomposition (HOSVD) as a practical example. Applications presented in the three- and four-dimensional MRI data demonstrate that HOSVD simultaneously exploited the correlations within spatial and temporal dimensions. Validations based on cardiac datasets indicate that the proposed method achieved comparable reconstruction accuracy with the low-rank matrix recovery methods and, outperformed the conventional sparse recovery methods. PMID:24901331
Sierra, M; Grasa, J; Muñoz, M J; Miana-Mena, F J; González, D
2017-04-01
A novel technique is proposed to predict force reduction in skeletal muscle due to fatigue under the influence of electrical stimulus parameters and muscle physiological characteristics. Twelve New Zealand white rabbits were divided in four groups ([Formula: see text]) to obtain the active force evolution of in vitro Extensor Digitorum Longus muscles for an hour of repeated contractions under different electrical stimulation patterns. Left and right muscles were tested, and a total of 24 samples were used to construct a response surface based in the proper generalized decomposition. After the response surface development, one additional rabbit was used to check the predictive potential of the technique. This multidimensional surface takes into account not only the decay of the maximum repeated peak force, but also the shape evolution of each contraction, muscle weight, electrical input signal and stimulation protocol. This new approach of the fatigue simulation challenge allows to predict, inside the multispace surface generated, the muscle response considering other stimulation patterns, different tissue weight, etc.
An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition
NASA Technical Reports Server (NTRS)
Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino
2013-01-01
Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.
NASA Astrophysics Data System (ADS)
Cromaz, M.; Campbell, C. M.; Clark, R. M.; Crawford, H. L.; Fallon, P.; Lee, I. Y.; Macchiavelli, A. O.; Wiens, A.; Riley, L.; Taniuchi, R.
2016-03-01
The performance of a gamma-ray tracking detector, such as those used in the GRETINA spectrometer, is dependent on its ability to accurately locate multiple interaction points in the Ge crystal. Interactions are located by observing both net and induced charge as a function of time on the detector's segmented contact. As multiple interactions are likely, linear combinations of basis signals, a set of simulated signals with unit charge deposited on a grid that spans the detector volume, are fit against the observed signal yielding the interaction positions. While the location of the primary interaction point was found to be good (σpos <= 2 mm) the location of secondary, lower energy interactions appear less reliable. To investigate this issue, we carried out a series of source-based coincidence measurements. These employed a collimated source and a secondary detector by which we could select single interaction events. Given these events originate from known positions, we can take them in combination to directly test the efficacy of the signal decomposition procedure. We will present a description of the method and preliminary results with a GRETINA quad detector. This work is supported by the U.S. Department of Energy under Contract No. DE-AC02-05CHI1231.
Seismic facies analysis based on self-organizing map and empirical mode decomposition
NASA Astrophysics Data System (ADS)
Du, Hao-kun; Cao, Jun-xing; Xue, Ya-juan; Wang, Xing-jian
2015-01-01
Seismic facies analysis plays an important role in seismic interpretation and reservoir model building by offering an effective way to identify the changes in geofacies inter wells. The selections of input seismic attributes and their time window have an obvious effect on the validity of classification and require iterative experimentation and prior knowledge. In general, it is sensitive to noise when waveform serves as the input data to cluster analysis, especially with a narrow window. To conquer this limitation, the Empirical Mode Decomposition (EMD) method is introduced into waveform classification based on SOM. We first de-noise the seismic data using EMD and then cluster the data using 1D grid SOM. The main advantages of this method are resolution enhancement and noise reduction. 3D seismic data from the western Sichuan basin, China, are collected for validation. The application results show that seismic facies analysis can be improved and better help the interpretation. The powerful tolerance for noise makes the proposed method to be a better seismic facies analysis tool than classical 1D grid SOM method, especially for waveform cluster with a narrow window.
Zyout, Imad; Togneri, Roberto
2015-01-01
Among the different and common mammographic signs of the early-stage breast cancer, the architectural distortion is the most difficult to be identified. In this paper, we propose a new multiscale statistical texture analysis to characterize the presence of architectural distortion by distinguishing between textural patterns of architectural distortion and normal breast parenchyma. The proposed approach, firstly, applies the bidimensional empirical mode decomposition algorithm to decompose each mammographic region of interest into a set of adaptive and data-driven two-dimensional intrinsic mode functions (IMF) layers that capture details or high-frequency oscillations of the input image. Then, a model-based approach is applied to IMF histograms to acquire the first order statistics. The normalized entropy measure is also computed from each IMF and used as a complementary textural feature for the recognition of architectural distortion patterns. For evaluating the proposed AD characterization approach, we used a mammographic dataset of 187 true positive regions (i.e. depicting architectural distortion) and 887 true negative (normal parenchyma) regions, extracted from the DDSM database. Using the proposed multiscale textural features and the nonlinear support vector machine classifier, the best classification performance, in terms of the area under the receiver operating characteristic curve (or Az value), achieved was 0.88.
Singular value decomposition based feature extraction technique for physiological signal analysis.
Chang, Cheng-Ding; Wang, Chien-Chih; Jiang, Bernard C
2012-06-01
Multiscale entropy (MSE) is one of the popular techniques to calculate and describe the complexity of the physiological signal. Many studies use this approach to detect changes in the physiological conditions in the human body. However, MSE results are easily affected by noise and trends, leading to incorrect estimation of MSE values. In this paper, singular value decomposition (SVD) is adopted to replace MSE to extract the features of physiological signals, and adopt the support vector machine (SVM) to classify the different physiological states. A test data set based on the PhysioNet website was used, and the classification results showed that using SVD to extract features of the physiological signal could attain a classification accuracy rate of 89.157%, which is higher than that using the MSE value (71.084%). The results show the proposed analysis procedure is effective and appropriate for distinguishing different physiological states. This promising result could be used as a reference for doctors in diagnosis of congestive heart failure (CHF) disease.
NASA Astrophysics Data System (ADS)
Sun, Y.; Lin, Y.; Hu, X.; Zhao, S.; Liu, S.; Tong, Q.; Helder, D.; Yan, L.
2017-09-01
Hyperspectral imaging system can obtain spectral and spatial information simultaneously with bandwidth to the level of 10 nm or even less. Therefore, hyperspectral remote sensing has the ability to detect some kinds of objects which can not be detected in wide-band remote sensing, making it becoming one of the hottest spots in remote sensing. In this study, under conditions with a fuzzy set of full constraints, Normalized Multi-Endmember Decomposition Method (NMEDM) for vegetation, water, and soil was proposed to reconstruct hyperspectral data using a large number of high-quality multispectral data and auxiliary spectral library data. This study considered spatial and temporal variation and decreased the calculation time required to reconstruct the hyper-spectral data. The results of spectral reconstruction based on NMEDM showed that the reconstructed data has good qualities and certain applications, which makes it possible to carry out spectral features identification. This method also extends the application of depth and breadth of remote sensing data, helping to explore the law between multispectral and hyperspectral data.
Regression-based adaptive sparse polynomial dimensional decomposition for sensitivity analysis
NASA Astrophysics Data System (ADS)
Tang, Kunkun; Congedo, Pietro; Abgrall, Remi
2014-11-01
Polynomial dimensional decomposition (PDD) is employed in this work for global sensitivity analysis and uncertainty quantification of stochastic systems subject to a large number of random input variables. Due to the intimate structure between PDD and Analysis-of-Variance, PDD is able to provide simpler and more direct evaluation of the Sobol' sensitivity indices, when compared to polynomial chaos (PC). Unfortunately, the number of PDD terms grows exponentially with respect to the size of the input random vector, which makes the computational cost of the standard method unaffordable for real engineering applications. In order to address this problem of curse of dimensionality, this work proposes a variance-based adaptive strategy aiming to build a cheap meta-model by sparse-PDD with PDD coefficients computed by regression. During this adaptive procedure, the model representation by PDD only contains few terms, so that the cost to resolve repeatedly the linear system of the least-square regression problem is negligible. The size of the final sparse-PDD representation is much smaller than the full PDD, since only significant terms are eventually retained. Consequently, a much less number of calls to the deterministic model is required to compute the final PDD coefficients.
Bearing fault diagnosis based on variational mode decomposition and total variation denoising
NASA Astrophysics Data System (ADS)
Zhang, Suofeng; Wang, Yanxue; He, Shuilong; Jiang, Zhansi
2016-07-01
Feature extraction plays an essential role in bearing fault detection. However, the measured vibration signals are complex and non-stationary in nature, and meanwhile impulsive signatures of rolling bearing are usually immersed in stochastic noise. Hence, a novel hybrid fault diagnosis approach is developed for the denoising and non-stationary feature extraction in this work, which combines well with the variational mode decomposition (VMD) and majoriation-minization based total variation denoising (TV-MM). The TV-MM approach is utilized to remove stochastic noise in the raw signal and to enhance the corresponding characteristics. Since the parameter λ is very important in TV-MM, the weighted kurtosis index is also proposed in this work to determine an appropriate λ used in TV-MM. The performance of the proposed hybrid approach is conducted through the analysis of the simulated and practical bearing vibration signals. Results demonstrate that the proposed approach has superior capability to detect roller bearing faults from vibration signals.
Mode decomposition based on crystallographic symmetry in the band-unfolding method
NASA Astrophysics Data System (ADS)
Ikeda, Yuji; Carreras, Abel; Seko, Atsuto; Togo, Atsushi; Tanaka, Isao
2017-01-01
The band-unfolding method is widely used to calculate the effective band structures of a disordered system from its supercell model. The unfolded band structures show the crystallographic symmetry of the underlying structure, where the difference of chemical components and the local atomic relaxation are ignored. However, it has still been difficult to decompose the unfolded band structures into the modes based on the crystallographic symmetry of the underlying structure, and therefore detailed analyses of the unfolded band structures have been restricted. In this study, a procedure to decompose the unfolded band structures according to the small representations (SRs) of the little groups is developed. The decomposition is performed using the projection operators for SRs derived from the group representation theory. The current method is employed to investigate the phonon band structure of disordered face-centered-cubic Cu0.75Au0.25 , which has large variations of atomic masses and force constants among the atomic sites due to the chemical disorder. In the unfolded phonon band structure, several peculiar behaviors such as discontinuous and split branches are found in the decomposed modes corresponding to specific SRs. They are found to occur because different combinations of the chemical elements contribute to different regions of frequency.
Multivariate Empirical Mode Decomposition Based Signal Analysis and Efficient-Storage in Smart Grid
Liu, Lu; Albright, Austin P; Rahimpour, Alireza; Guo, Jiandong; Qi, Hairong; Liu, Yilu
2017-01-01
Wide-area-measurement systems (WAMSs) are used in smart grid systems to enable the efficient monitoring of grid dynamics. However, the overwhelming amount of data and the severe contamination from noise often impede the effective and efficient data analysis and storage of WAMS generated measurements. To solve this problem, we propose a novel framework that takes advantage of Multivariate Empirical Mode Decomposition (MEMD), a fully data-driven approach to analyzing non-stationary signals, dubbed MEMD based Signal Analysis (MSA). The frequency measurements are considered as a linear superposition of different oscillatory components and noise. The low-frequency components, corresponding to the long-term trend and inter-area oscillations, are grouped and compressed by MSA using the mean shift clustering algorithm. Whereas, higher-frequency components, mostly noise and potentially part of high-frequency inter-area oscillations, are analyzed using Hilbert spectral analysis and they are delineated by statistical behavior. By conducting experiments on both synthetic and real-world data, we show that the proposed framework can capture the characteristics, such as trends and inter-area oscillation, while reducing the data storage requirements
Putting domain decomposition at the heart of a mesh-based simulation process
NASA Astrophysics Data System (ADS)
Chow, Peter; Addison, Clifford
2002-12-01
In computational mechanics analyses such as those in computational fluid dynamics and computational structure mechanics, some 60-90% of total modelling time is taken by specifying and creating the model of the geometry and mesh. The rest of the time is spent in actual analyses and interpreting the results. This is especially true for industries such as aerospace and electronics, where 3D geometrically complex models with multiple physical processes are common. Advances in computational hardware and software have tended to increase the proportion of time spent in model creation, partly because such advances have made it feasible to solve hard and complex geometry problems in a timely fashion. This paper shows one way to exploit the advances in computation to reduce the model creation time and potentially the overall modelling time, namely the use of domain decomposition to define consistent and coherent global models based on existing component geometry and mesh models. In keeping with existing modelling processes the re-engineering cost for the process is minimal.
A novel image watermarking method based on singular value decomposition and digital holography
NASA Astrophysics Data System (ADS)
Cai, Zhishan
2016-10-01
According to the information optics theory, a novel watermarking method based on Fourier-transformed digital holography and singular value decomposition (SVD) is proposed in this paper. First of all, a watermark image is converted to a digital hologram using the Fourier transform. After that, the original image is divided into many non-overlapping blocks. All the blocks and the hologram are decomposed using SVD. The singular value components of the hologram are then embedded into the singular value components of each block using an addition principle. Finally, SVD inverse transformation is carried out on the blocks and hologram to generate the watermarked image. The watermark information embedded in each block is extracted at first when the watermark is extracted. After that, an averaging operation is carried out on the extracted information to generate the final watermark information. Finally, the algorithm is simulated. Furthermore, to test the encrypted image's resistance performance against attacks, various attack tests are carried out. The results show that the proposed algorithm has very good robustness against noise interference, image cut, compression, brightness stretching, etc. In particular, when the image is rotated by a large angle, the watermark information can still be extracted correctly.
NASA Astrophysics Data System (ADS)
E, Jianwei; Bao, Yanling; Ye, Jimin
2017-10-01
As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.
BEHRENS JR.,RICHARD; MINIER,LEANNA M.G.
1999-10-25
A study to characterize the low-temperature reactive processes for o-AP and an AP/HTPB-based propellant (class 1.3) is being conducted in the laboratory using the techniques of simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) and scanning electron microscopy (SEM). The results presented in this paper are a follow up of the previous work that showed the overall decomposition to be complex and controlled by both physical and chemical processes. The decomposition is characterized by the occurrence of one major event that consumes up to {approx}35% of the AP, depending upon particle size, and leaves behind a porous agglomerate of AP. The major gaseous products released during this event include H{sub 2}O, O{sub 2}, Cl{sub 2}, N{sub 2}O and HCl. The recent efforts provide further insight into the decomposition processes for o-AP. The temporal behaviors of the gas formation rates (GFRs) for the products indicate that the major decomposition event consists of three chemical channels. The first and third channels are affected by the pressure in the reaction cell and occur at the surface or in the gas phase above the surface of the AP particles. The second channel is not affected by pressure and accounts for the solid-phase reactions characteristic of o-AP. The third channel involves the interactions of the decomposition products with the surface of the AP. SEM images of partially decomposed o-AP provide insight to how the morphology changes as the decomposition progresses. A conceptual model has been developed, based upon the STMBMS and SEM results, that provides a basic description of the processes. The thermal decomposition characteristics of the propellant are evaluated from the identities of the products and the temporal behaviors of their GFRs. First, the volatile components in the propellant evolve from the propellant as it is heated. Second, the hot AP (and HClO{sub 4}) at the AP-binder interface oxidize the binder through reactions that
A Graph-Based Recovery and Decomposition of Swanson’s Hypothesis using Semantic Predications
Cameron, Delroy; Bodenreider, Olivier; Yalamanchili, Hima; Danh, Tu; Vallabhaneni, Sreeram; Thirunarayan, Krishnaprasad; Sheth, Amit P.; Rindflesch, Thomas C.
2014-01-01
Objectives This paper presents a methodology for recovering and decomposing Swanson’s Raynaud Syndrome–Fish Oil Hypothesis semi-automatically. The methodology leverages the semantics of assertions extracted from biomedical literature (called semantic predications) along with structured background knowledge and graph-based algorithms to semi-automatically capture the informative associations originally discovered manually by Swanson. Demonstrating that Swanson’s manually intensive techniques can be undertaken semi-automatically, paves the way for fully automatic semantics-based hypothesis generation from scientific literature. Methods Semantic predications obtained from biomedical literature allow the construction of labeled directed graphs which contain various associations among concepts from the literature. By aggregating such associations into informative subgraphs, some of the relevant details originally articulated by Swanson has been uncovered. However, by leveraging background knowledge to bridge important knowledge gaps in the literature, a methodology for semi-automatically capturing the detailed associations originally explicated in natural language by Swanson has been developed. Results Our methodology not only recovered the 3 associations commonly recognized as Swanson’s Hypothesis, but also decomposed them into an additional 16 detailed associations, formulated as chains of semantic predications. Altogether, 14 out of the 19 associations that can be attributed to Swanson were retrieved using our approach. To the best of our knowledge, such an in-depth recovery and decomposition of Swanson’s Hypothesis has never been attempted. Conclusion In this work therefore, we presented a methodology for semi- automatically recovering and decomposing Swanson’s RS-DFO Hypothesis using semantic representations and graph algorithms. Our methodology provides new insights into potential prerequisites for semantics-driven Literature-Based Discovery (LBD
Catalytic effects of inorganic acids on the decomposition of ammonium nitrate.
Sun, Jinhua; Sun, Zhanhui; Wang, Qingsong; Ding, Hui; Wang, Tong; Jiang, Chuansheng
2005-12-09
In order to evaluate the catalytic effects of inorganic acids on the decomposition of ammonium nitrate (AN), the heat releases of decomposition or reaction of pure AN and its mixtures with inorganic acids were analyzed by a heat flux calorimeter C80. Through the experiments, the different reaction mechanisms of AN and its mixtures were analyzed. The chemical reaction kinetic parameters such as reaction order, activation energy and frequency factor were calculated with the C80 experimental results for different samples. Based on these parameters and the thermal runaway models (Semenov and Frank-Kamenestkii model), the self-accelerating decomposition temperatures (SADTs) of AN and its mixtures were calculated and compared. The results show that the mixtures of AN with acid are more unsteady than pure AN. The AN decomposition reaction is catalyzed by acid. The calculated SADTs of AN mixtures with acid are much lower than that of pure AN.
Xu, Libin; Newcomb, Martin
2005-11-11
[Reaction: see text].A model for glycol radicals was employed in laser flash photolysis kinetic studies of catalysis of the fragmentation of a methoxy group adjacent to an alpha-hydroxy radical center. Photolysis of a phenylselenylmethylcyclopropane precursor gave a cyclopropylcarbinyl radical that rapidly ring opened to the target alpha-hydroxy-beta-methoxy radical (3). Heterolysis of the methoxy group in 3 gave an enolyl radical (4a) or an enol ether radical cation (4b), depending upon pH. Radicals 4 contain a 2,2-diphenylcyclopropane reporter group, and they rapidly opened to give UV-observable diphenylalkyl radicals as the final products. No heterolysis was observed for radical 3 under neutral conditions. In basic aqueous acetonitrile solutions, specific base catalysis of the heterolysis was observed; the pK(a) of radical 3 was determined to be 12.5 from kinetic titration plots, and the ketyl radical formed by deprotonation of 3 eliminated methoxide with a rate constant of 5 x 10(7) s(-1). In the presence of carboxylic acids in acetonitrile solutions, radical 3 eliminated methanol in a general acid-catalyzed reaction, and rate constants for protonation of the methoxy group in 3 by several acids were measured. Radical 3 also reacted by fragmentation of methoxide in Lewis-acid-catalyzed heterolysis reactions; ZnBr2, Sc(OTf)3, and BF3 were found to be efficient catalysts. Catalytic rate constants for the heterolysis reactions were in the range of 3 x 10(4) to 2 x 10(6) s(-1). The Lewis-acid-catalyzed heterolysis reactions are fast enough for kinetic competence in coenzyme B12 dependent enzyme-catalyzed reactions of glycols, and Lewis-acid-catalyzed cleavages of beta-ethers in radicals might be applied in synthetic reactions.
Carril, Mónica; SanMartin, Raul; Churruca, Fátima; Tellitu, Imanol; Domínguez, Esther
2005-10-27
[reaction: see text] A new route to oxcarbazepine (Trileptal), the most widely prescribed antiepileptic drug, starting from commercially available 2'-aminoacetophenone and 1,2-dibromobenzene, is reported. The sequentially accomplished key steps are palladium-catalyzed intermolecular alpha-arylation of ketone enolates and intramolecular N-arylation reactions. After several experiments to establish the best conditions for both arylation processes, the target oxcarbazepine is obtained in a satisfactory overall yield, minimizing the number of steps and employing scalable catalytic procedures developed in partially aqueous media.
Implementation of material decomposition using an EMCCD and CMOS-based micro-CT system
NASA Astrophysics Data System (ADS)
Podgorsak, Alexander R.; Nagesh, S. V. Setlur; Bednarek, Daniel R.; Rudin, Stephen; Ionita, Ciprian N.
2017-03-01
This project assessed the effectiveness of using two different detectors to obtain dual-energy (DE) micro-CT data for the carrying out of material decomposition. A micro-CT coupled to either a complementary metal-oxide semiconductor (CMOS) or an electron multiplying CCD (EMCCD) detector was used to acquire image data of a 3D-printed phantom with channels filled with different materials. At any instance, materials such as iohexol contrast agent, water, and platinum were selected to make up the scanned object. DE micro-CT data was acquired, and slices of the scanned object were differentiated by material makeup. The success of the decomposition was assessed quantitatively through the computation of percentage normalized root-mean-square error (%NRMSE). Our results indicate a successful decomposition of iohexol for both detectors (%NRMSE values of 1.8 for EMCCD, 2.4 for CMOS), as well as platinum (%NRMSE value of 4.7). The CMOS detector performed material decomposition on air and water on average with 7 times more %NRMSE, possibly due to the decreased sensitivity of the CMOS system. Material decomposition showed the potential to differentiate between materials such as the iohexol and platinum, perhaps opening the door for its use in the neurovascular anatomical region. Work supported by Toshiba America Medical Systems, and partially supported by NIH grant 2R01EB002873.
Implementation of material decomposition using an EMCCD and CMOS-based micro-CT system.
Podgorsak, Alexander R; Nagesh, Sv Setlur; Bednarek, Daniel R; Rudin, Stephen; Ionita, Ciprian N
2017-02-11
This project assessed the effectiveness of using two different detectors to obtain dual-energy (DE) micro-CT data for the carrying out of material decomposition. A micro-CT coupled to either a complementary metal-oxide semiconductor (CMOS) or an electron multiplying CCD (EMCCD) detector was used to acquire image data of a 3D-printed phantom with channels filled with different materials. At any instance, materials such as iohexol contrast agent, water, and platinum were selected to make up the scanned object. DE micro-CT data was acquired, and slices of the scanned object were differentiated by material makeup. The success of the decomposition was assessed quantitatively through the computation of percentage normalized root-mean-square error (%NRMSE). Our results indicate a successful decomposition of iohexol for both detectors (%NRMSE values of 1.8 for EMCCD, 2.4 for CMOS), as well as platinum (%NRMSE value of 4.7). The CMOS detector performed material decomposition on air and water on average with 7 times more %NRMSE, possibly due to the decreased sensitivity of the CMOS system. Material decomposition showed the potential to differentiate between materials such as the iohexol and platinum, perhaps opening the door for its use in the neurovascular anatomical region. Work supported by Toshiba America Medical Systems, and partially supported by NIH grant 2R01EB002873.
Robust x-ray based material identification using multi-energy sinogram decomposition
NASA Astrophysics Data System (ADS)
Yuan, Yaoshen; Tracey, Brian; Miller, Eric
2016-05-01
There is growing interest in developing X-ray computed tomography (CT) imaging systems with improved ability to discriminate material types, going beyond the attenuation imaging provided by most current systems. Dual- energy CT (DECT) systems can partially address this problem by estimating Compton and photoelectric (PE) coefficients of the materials being imaged, but DECT is greatly degraded by the presence of metal or other materials with high attenuation. Here we explore the advantages of multi-energy CT (MECT) systems based on photon-counting detectors. The utility of MECT has been demonstrated in medical applications where photon- counting detectors allow for the resolution of absorption K-edges. Our primary concern is aviation security applications where K-edges are rare. We simulate phantoms with differing amounts of metal (high, medium and low attenuation), both for switched-source DECT and for MECT systems, and include a realistic model of detector energy 0 resolution. We extend the DECT sinogram decomposition method of Ying et al. to MECT, allowing estimation of separate Compton and photoelectric sinograms. We furthermore introduce a weighting based on a quadratic approximation to the Poisson likelihood function that deemphasizes energy bins with low signal. Simulation results show that the proposed approach succeeds in estimating material properties even in high-attenuation scenarios where the DECT method fails, improving the signal to noise ratio of reconstructions by over 20 dB for the high-attenuation phantom. Our work demonstrates the potential of using photon counting detectors for stably recovering material properties even when high attenuation is present, thus enabling the development of improved scanning systems.
LLNL demonstration of base hydrolysate decomposition in a 0.035 gallon per minute scale reactor
Cena, R.J.; Thorsness, C.B.; Coburn, T.; Watkins, B.E.
1994-06-01
The Lawrence Livermore National Laboratory (LLNL) has built and operated a pilot plant for processing oil shale using recirculating hot solids. This pilot plant, was adapted in 1993 to demonstrate the feasibility of decomposing base hydrolysate, a mixture of sodium nitrite, sodium formate and other constituents. This material is the waste stream from the base hydrolysis process for destruction of energetic materials, being studied by researchers at Los Alamos National Laboratory (LANL). In the Livermore process, the waste feed is thermally treated in a moving packed bed of ceramic spheres, where constituents in the waste decompose, in the presence of carbon dioxide, to form solid sodium carbonate and a suite of gases including: methane, carbon monoxide, oxygen, nitrogen oxides, ammonia and possibly molecular nitrogen. The authors performed an extended one day (8 hour) test of the solids recirculation system, with continuous injection of approximately 0.035 gal/min of waste for period of seven hours. Continuous on-line gas analysis was invaluable in tracking the progress of the experiment and quantifying the decomposition products. Analyses showed the primary solid product, collected in the lift exit cyclone, was indeed sodium carbonate, as expected. For the reactor condition studied in this test, N{sub 2}O was found to be the primary nitrogen bearing gas species. However, other experimental results indicate that in a more oxidizing environment, with longer residence times, the production of N{sub 2}O can be limited. In the test, approximately equal quantities of ammonia and nitrogen bearing oxide gases were produced (NO, NO{sub 2} and N{sub 2}O).
NASA Astrophysics Data System (ADS)
Afra, Sardar; Gildin, Eduardo
2016-09-01
Parameter estimation through robust parameterization techniques has been addressed in many works associated with history matching and inverse problems. Reservoir models are in general complex, nonlinear, and large-scale with respect to the large number of states and unknown parameters. Thus, having a practical approach to replace the original set of highly correlated unknown parameters with non-correlated set of lower dimensionality, that captures the most significant features comparing to the original set, is of high importance. Furthermore, de-correlating system's parameters while keeping the geological description intact is critical to control the ill-posedness nature of such problems. We introduce the advantages of a new low dimensional parameterization approach for reservoir characterization applications utilizing multilinear algebra based techniques like higher order singular value decomposition (HOSVD). In tensor based approaches like HOSVD, 2D permeability images are treated as they are, i.e., the data structure is kept as it is, whereas in conventional dimensionality reduction algorithms like SVD data has to be vectorized. Hence, compared to classical methods, higher redundancy reduction with less information loss can be achieved through decreasing present redundancies in all dimensions. In other words, HOSVD approximation results in a better compact data representation with respect to least square sense and geological consistency in comparison with classical algorithms. We examined the performance of the proposed parameterization technique against SVD approach on the SPE10 benchmark reservoir model as well as synthetic channelized permeability maps to demonstrate the capability of the proposed method. Moreover, to acquire statistical consistency, we repeat all experiments for a set of 1000 unknown geological samples and provide comparison using RMSE analysis. Results prove that, for a fixed compression ratio, the performance of the proposed approach
Optimization of dual-energy CT acquisitions for proton therapy using projection-based decomposition.
Vilches-Freixas, Gloria; Létang, Jean Michel; Ducros, Nicolas; Rit, Simon
2017-09-01
Dual-energy computed tomography (DECT) has been presented as a valid alternative to single-energy CT to reduce the uncertainty of the conversion of patient CT numbers to proton stopping power ratio (SPR) of tissues relative to water. The aim of this work was to optimize DECT acquisition protocols from simulations of X-ray images for the treatment planning of proton therapy using a projection-based dual-energy decomposition algorithm. We have investigated the effect of various voltages and tin filtration combinations on the SPR map accuracy and precision, and the influence of the dose allocation between the low-energy (LE) and the high-energy (HE) acquisitions. For all spectra combinations, virtual CT projections of the Gammex phantom were simulated with a realistic energy-integrating detector response model. Two situations were simulated: an ideal case without noise (infinite dose) and a realistic situation with Poisson noise corresponding to a 20 mGy total central dose. To determine the optimal dose balance, the proportion of LE-dose with respect to the total dose was varied from 10% to 90% while keeping the central dose constant, for four dual-energy spectra. SPR images were derived using a two-step projection-based decomposition approach. The ranges of 70 MeV, 90 MeV, and 100 MeV proton beams onto the adult female (AF) reference computational phantom of the ICRP were analytically determined from the reconstructed SPR maps. The energy separation between the incident spectra had a strong impact on the SPR precision. Maximizing the incident energy gap reduced image noise. However, the energy gap was not a good metric to evaluate the accuracy of the SPR. In terms of SPR accuracy, a large variability of the optimal spectra was observed when studying each phantom material separately. The SPR accuracy was almost flat in the 30-70% LE-dose range, while the precision showed a minimum slightly shifted in favor of lower LE-dose. Photon noise in the SPR images (20 mGy dose
Kolb, Peter; Caflisch, Amedeo
2006-12-14
The computer program DAIM (Decomposition and Identification of Molecules) has been developed to automatically break up compounds in small-molecule libraries for fragment-based docking as well as database analysis. Here, DAIM is evaluated on 130 ligands derived from known crystal structures of ligand-protein complexes. The decomposition and a new fingerprint-based identification technique are used to select anchor fragments for docking. The docking results show that the DAIM selection is superior to size-based or random selection of fragments. To evaluate the usefulness for analyzing the fragment composition of a large library, DAIM is applied to a collection of about 1.85 million commercially available compounds. Interestingly, it is found that the set of most frequent cyclic and acyclic fragments originating from the decomposition of the 1.85 million molecules shows a large overlap with the most frequent fragments in a library of 5120 known drugs. DAIM has been successfully used in the in silico screening for inhibitors of beta-secretase and EphB4 kinase by fragment-based high-throughput docking. Possible future applications for de novo ligand design are briefly discussed.
Li, Feng; Yang, Limin; Chen, Mingqin; Qian, Yi; Tang, Bo
2013-03-15
A novel, simple, and versatile amperometric sensing platform was developed based on HRP-mimicking DNAzyme-catalyzed template-guided deposition of polyaniline (PANI). Pb(2+) was chosen as a model to demonstrate the proof-of-concept of our approach. The Pb(2+) aptamer was first self-assembled on the electrode surface. Upon addition of Pb(2+), Pb(2+) bound to its aptamer to form G-quadruplex (G4). HRP-mimicking DNAzyme with peroxidase catalytic activity was successfully generated after hemin was efficiently intercalated into the G4 structure. Subsequently, HRP-mimicking DNAzyme catalyzed oxidation of aniline to PANI with H(2)O(2) exclusively at the G4 structures, which lead to a readily measurable "turn-on" electrochemical signal. The constructed platform exhibited a good linear response toward Pb(2+) over a wide range of concentration from 1.0×10(-9) M to 1.0×10(-6) M with the detection limit of 5.0×10(-10) M. The high performance DNAzyme-based strategy can be further extended to quantify a wide variety of analytes.
Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing
NASA Astrophysics Data System (ADS)
Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa
2017-02-01
Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture—for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments—as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series—daily Poaceae pollen concentrations over the period 2006-2014—was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.
A patch-based tensor decomposition algorithm for M-FISH image classification.
Wang, Min; Huang, Ting-Zhu; Li, Jingyao; Wang, Yu-Ping
2017-06-01
Multiplex-fluorescence in situ hybridization (M-FISH) is a chromosome imaging technique which can be used to detect chromosomal abnormalities such as translocations, deletions, duplications, and inversions. Chromosome classification from M-FISH imaging data is a key step to implement the technique. In the classified M-FISH image, each pixel in a chromosome is labeled with a class index and drawn with a pseudo-color so that geneticists can easily conduct diagnosis, for example, identifying chromosomal translocations by examining color changes between chromosomes. However, the information of pixels in a neighborhood is often overlooked by existing approaches. In this work, we assume that the pixels in a patch belong to the same class and use the patch to represent the center pixel's class information, by which we can use the correlations of neighboring pixels and the structural information across different spectral channels for the classification. On the basis of assumption, we propose a patch-based classification algorithm by using higher order singular value decomposition (HOSVD). The developed method has been tested on a comprehensive M-FISH database that we established, demonstrating improved performance. When compared with other pixel-wise M-FISH image classifiers such as fuzzy c-means clustering (FCM), adaptive fuzzy c-means clustering (AFCM), improved adaptive fuzzy c-means clustering (IAFCM), and sparse representation classification (SparseRC) methods, the proposed method gave the highest correct classification ratio (CCR), which can translate into improved diagnosis of genetic diseases and cancers. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.
Kim, Jae In; Na, Sungsoo; Eom, Kilho
2011-01-15
Normal mode analysis (NMA) with coarse-grained model, such as elastic network model (ENM), has allowed the quantitative understanding of protein dynamics. As the protein size is increased, there emerges the expensive computational process to find the dynamically important low-frequency normal modes due to diagonalization of massive Hessian matrix. In this study, we have provided the domain decomposition-based structural condensation method that enables the efficient computations on low-frequency motions. Specifically, our coarse-graining method is established by coupling between model condensation (MC; Eom et al., J Comput Chem 2007, 28, 1400) and component mode synthesis (Kim et al., J Chem Theor Comput 2009, 5, 1931). A protein structure is first decomposed into substructural units, and then each substructural unit is coarse-grained by MC. Once the NMA is implemented to coarse-grained substructural units, normal modes and natural frequencies for each coarse-grained substructural unit are assembled by using geometric constraints to provide the normal modes and natural frequencies for whole protein structure. It is shown that our coarse-graining method enhances the computational efficiency for analysis of large protein complexes. It is clearly suggested that our coarse-graining method provides the B-factors of 100 large proteins, quantitatively comparable with those obtained from original NMA, with computational efficiency. Moreover, the collective behaviors and/or the correlated motions for model proteins are well delineated by our suggested coarse-grained models, quantitatively comparable with those computed from original NMA. It is implied that our coarse-grained method enables the computationally efficient studies on conformational dynamics of large protein complex.
Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing
NASA Astrophysics Data System (ADS)
Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa
2016-08-01
Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture—for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments—as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series—daily Poaceae pollen concentrations over the period 2006-2014—was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.
Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.
Rojo, Jesús; Rivero, Rosario; Romero-Morte, Jorge; Fernández-González, Federico; Pérez-Badia, Rosa
2017-02-01
Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture-for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments-as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series-daily Poaceae pollen concentrations over the period 2006-2014-was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.
Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.; Balboa, Alex; Troya, Diego; Guo, Weiwei; Sharp, Conor H.; Senanayake, Sanjaya D.; Morris, John R.; Hill, Craig L.; Frenkel, Anatoly I.
2016-12-30
Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination of DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.
Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.; ...
2016-12-30
Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less
Plonka, Anna M; Wang, Qi; Gordon, Wesley O; Balboa, Alex; Troya, Diego; Guo, Weiwei; Sharp, Conor H; Senanayake, Sanjaya D; Morris, John R; Hill, Craig L; Frenkel, Anatoly I
2017-01-18
Zr-based metal organic frameworks (MOFs) have been recently shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. We report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination of DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. These experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.
Pasini, Thomas; Solinas, Gavino; Zanotti, Valerio; Albonetti, Stefania; Cavani, Fabrizio; Vaccari, Angelo; Mazzanti, Andrea; Ranieri, Silvia; Mazzoni, Rita
2014-07-14
The bio-based substrate and target product 2,5-bishydroxymethylfuran (BHMF) demonstrated to influence the reaction kinetics in the homogeneous reduction of 5-hydroxymethylfurfural (HMF) catalyzed by the Ru-based Shvo's catalyst. A combined experimental and computational study supports an important role of the -CH2OH moiety which may be involved in the catalytic cycle toward the formation of different intermediates from HMF and BHMF. The reaction is selective and leads to quantitative formation of BHMF working under mild conditions. Furthermore, an optimized recycling procedure which avoids the use of water, allows recover and reuse of the catalyst without loss of activity. The mechanistic insights from this work may be extended to provide a general description of the chemistry of the Shvo's catalyst feeding further bio-based molecules.
NASA Astrophysics Data System (ADS)
Chen, Yi-Feng; Atal, Kiran; Xie, Sheng-Quan; Liu, Quan
2017-08-01
Objective. Accurate and efficient detection of steady-state visual evoked potentials (SSVEP) in electroencephalogram (EEG) is essential for the related brain-computer interface (BCI) applications. Approach. Although the canonical correlation analysis (CCA) has been applied extensively and successfully to SSVEP recognition, the spontaneous EEG activities and artifacts that often occur during data recording can deteriorate the recognition performance. Therefore, it is meaningful to extract a few frequency sub-bands of interest to avoid or reduce the influence of unrelated brain activity and artifacts. This paper presents an improved method to detect the frequency component associated with SSVEP using multivariate empirical mode decomposition (MEMD) and CCA (MEMD-CCA). EEG signals from nine healthy volunteers were recorded to evaluate the performance of the proposed method for SSVEP recognition. Main results. We compared our method with CCA and temporally local multivariate synchronization index (TMSI). The results suggest that the MEMD-CCA achieved significantly higher accuracy in contrast to standard CCA and TMSI. It gave the improvements of 1.34%, 3.11%, 3.33%, 10.45%, 15.78%, 18.45%, 15.00% and 14.22% on average over CCA at time windows from 0.5 s to 5 s and 0.55%, 1.56%, 7.78%, 14.67%, 13.67%, 7.33% and 7.78% over TMSI from 0.75 s to 5 s. The method outperformed the filter-based decomposition (FB), empirical mode decomposition (EMD) and wavelet decomposition (WT) based CCA for SSVEP recognition. Significance. The results demonstrate the ability of our proposed MEMD-CCA to improve the performance of SSVEP-based BCI.
Microorganisms detected by enzyme-catalyzed reaction
NASA Technical Reports Server (NTRS)
Vango, S. P.; Weetall, H. H.; Weliky, N.
1966-01-01
Enzymes detect the presence of microorganisms in soils. The enzyme lysozymi is used to release the enzyme catalase from the microorganisms in a soil sample. The catalase catalyzes the decomposition of added hydrogen peroxide to produce oxygen which is detected manometrically. The partial pressure of the oxygen serves as an index of the samples bacteria content.
Density-dependent liquid nitromethane decomposition: molecular dynamics simulations based on ReaxFF.
Rom, Naomi; Zybin, Sergey V; van Duin, Adri C T; Goddard, William A; Zeiri, Yehuda; Katz, Gil; Kosloff, Ronnie
2011-09-15
The decomposition mechanism of hot liquid nitromethane at various compressions was studied using reactive force field (ReaxFF) molecular dynamics simulations. A competition between two different initial thermal decomposition schemes is observed, depending on compression. At low densities, unimolecular C-N bond cleavage is the dominant route, producing CH(3) and NO(2) fragments. As density and pressure rise approaching the Chapman-Jouget detonation conditions (∼30% compression, >2500 K) the dominant mechanism switches to the formation of the CH(3)NO fragment via H-transfer and/or N-O bond rupture. The change in the decomposition mechanism of hot liquid NM leads to a different kinetic and energetic behavior, as well as products distribution. The calculated density dependence of the enthalpy change correlates with the change in initial decomposition reaction mechanism. It can be used as a convenient and useful global parameter for the detection of reaction dynamics. Atomic averaged local diffusion coefficients are shown to be sensitive to the reactions dynamics, and can be used to distinguish between time periods where chemical reactions occur and diffusion-dominated, nonreactive time periods.
NASA Astrophysics Data System (ADS)
Baykara, N. A.; Gürvit, Ercan
2014-10-01
The application of the Fluctuationlessness theorem to the remainder term of Taylor decomposition on which both sides are integrated has been already worked on. In this work the novelty brought to the previous work is to apply the Fluctuationlessness theorem to the remainder part which, itself also is decomposed in Taylor sense.
Naureen, Rizwana; Tariq, Muhammad; Yusoff, Ismail; Chowdhury, Ahmed Jalal Khan; Ashraf, Muhammad Aqeel
2015-05-01
Methyl esters from vegetable oils have attracted a great deal of interest as substitute for petrodiesel to reduce dependence on imported petroleum and provide an alternate and sustainable source for fuel with more benign environmental properties. In the present study biodiesel was prepared from sunflower seed oil by transesterification by alkali-catalyzed methanolysis. The fuel properties of sunflower oil biodiesel were determined and discussed in the light of ASTM D6751 standards for biodiesel. The sunflower oil biodiesel was chemically characterized with analytical techniques like FT-IR, and NMR ((1)H and (13)C). The chemical composition of sunflower oil biodiesel was determined by GC-MS. Various fatty acid methyl esters (FAMEs) were identified by retention time data and verified by mass fragmentation patterns. The percentage conversion of triglycerides to the corresponding methyl esters determined by (1)H NMR was 87.33% which was quite in good agreement with the practically observed yield of 85.1%.
Naureen, Rizwana; Tariq, Muhammad; Yusoff, Ismail; Chowdhury, Ahmed Jalal Khan; Ashraf, Muhammad Aqeel
2014-01-01
Methyl esters from vegetable oils have attracted a great deal of interest as substitute for petrodiesel to reduce dependence on imported petroleum and provide an alternate and sustainable source for fuel with more benign environmental properties. In the present study biodiesel was prepared from sunflower seed oil by transesterification by alkali-catalyzed methanolysis. The fuel properties of sunflower oil biodiesel were determined and discussed in the light of ASTM D6751 standards for biodiesel. The sunflower oil biodiesel was chemically characterized with analytical techniques like FT-IR, and NMR (1H and 13C). The chemical composition of sunflower oil biodiesel was determined by GC–MS. Various fatty acid methyl esters (FAMEs) were identified by retention time data and verified by mass fragmentation patterns. The percentage conversion of triglycerides to the corresponding methyl esters determined by 1H NMR was 87.33% which was quite in good agreement with the practically observed yield of 85.1%. PMID:25972756
Hierarchical decomposition of burn body diagram based on cutaneous functional units and its utility.
Richard, Reg; Jones, John A; Parshley, Philip
2015-01-01
A burn body diagram (BBD) is a common feature used in the delivery of burn care for estimating the TBSA burn as well as calculating fluid resuscitation and nutritional requirements, wound healing, and rehabilitation intervention. However, little change has occurred for over seven decades in the configuration of the BBD. The purpose of this project was to develop a computerized model using hierarchical decomposition (HD) to more precisely determine the percentage burn within a BBD based on cutaneous functional units (CFUs). HD is a process by which a system is degraded into smaller parts that are more precise in their use. CFUs were previously identified fields of the skin involved in the range of motion. A standard Lund/Browder (LB) BBD template was used as the starting point to apply the CFU segments. LB body divisions were parceled down into smaller body area divisions through a HD process based on the CFU concept. A numerical pattern schema was used to label the various segments in a cephalo/caudal, anterior/posterior, medial/lateral manner. Hand/fingers were divided based on anatomical landmarks and known cutaneokinematic function. The face was considered using aesthetic units. Computer code was written to apply the numeric hierarchical schema to CFUs and applied within the context of the surface area graphic evaluation BBD program. Each segmented CFU was coded to express 100% of itself. The CFU/HD method refined the standard LB diagram from 13 body segments and 33 subdivisions into 182 isolated CFUs. Associated CFUs were reconstituted into 219 various surface area combinations totaling 401 possible surface segments. The CFU/HD schema of the body surface mapping is applicable to measuring and calculating percent wound healing in a more precise manner. It eliminates subjective assessment of the percentage wound healing and the need for additional devices such as planimetry. The development of CFU/HD body mapping schema has rendered a technologically advanced
Novel syn intramolecular pathway in base-catalyzed 1,2-elimination reactions of beta-acetoxy esters.
Mohrig, Jerry R; Carlson, Hans K; Coughlin, Jane M; Hofmeister, Gretchen E; McMartin, Lea A; Rowley, Elizabeth G; Trimmer, Elizabeth E; Wild, Andrew J; Schultz, Steve C
2007-02-02
As part of a comprehensive investigation of electronic effects on the stereochemistry of base-catalyzed 1,2-elimination reactions, we observed a new syn intramolecular pathway in the elimination of acetic acid from beta-acetoxy esters and thioesters. 1H and 2H NMR investigation of reactions using stereospecifically labeled tert-butyl (2R*,3R*)-3-acetoxy-2,3-2H2-butanoate (1) and its (2R*,3S*) diastereomer (2) shows that 23 +/- 2% syn elimination occurs. The elimination reactions were catalyzed with KOH or (CH3)4NOH in ethanol/water under rigorously non-ion-pairing conditions. By contrast, the more sterically hindered beta-trimethylacetoxy ester produces only 6 +/- 1% syn elimination. These data strongly support an intramolecular (Ei) syn path for elimination of acetic acid, most likely through the oxyanion produced by nucleophilic attack at the carbonyl carbon of the beta-acetoxy group. The analogous thioesters, S-tert-butyl (2R*,3R*)-3-acetoxy-2,3-2H2-butanethioate (3) and its (2R*,3S*) diastereomer (4), showed 18 +/- 2% syn elimination, whereas the beta-trimethylacetoxy substrate gave 5 +/- 1% syn elimination. The more acidic thioester substrates do not produce an increased amount of syn stereoselectivity even though their elimination reactions are at the E1cb interface.
NASA Astrophysics Data System (ADS)
Bhattacharya, A.; Guo, Y. Q.; Bernstein, E. R.
2009-11-01
Unimolecular excited electronic state decomposition of novel high nitrogen content energetic molecules, such as 3,3'-azobis(6-amino-1,2,4,5-tetrazine)-mixed N-oxides (DAATO3.5), 3-amino-6-chloro-1,2,4,5-tetrazine-2,4-dioxide (ACTO), and 3,6-diamino-1,2,4,5-tetrazine-1,4-dioxde (DATO), is investigated. Although these molecules are based on N-oxides of a tetrazine aromatic heterocyclic ring, their decomposition behavior distinctly differs from that of bare tetrazine, in which N2 and HCN are produced as decomposition products through a concerted dissociation mechanism. NO is observed to be an initial decomposition product from all tetrazine-N-oxide based molecules from their low lying excited electronic states. The NO product from DAATO3.5 and ACTO is rotationally cold (20 K) and vibrationally hot (1200 K), while the NO product from DATO is rotationally hot (50 K) and vibrationally cold [only the (0-0) vibronic transition of NO is observed]. DAATO3.5 and ACTO primarily differ from DATO with regard to molecular structure, by the relative position of oxygen atom attachment to the tetrazine ring. Therefore, the relative position of oxygen in tetrazine-N-oxides is proposed to play an important role in their energetic behavior. N2O is ruled out as an intermediate precursor of the NO product observed from all three molecules. Theoretical calculations at CASMP2/CASSCF level of theory predict a ring contraction mechanism for generation of the initial NO product from these molecules. The ring contraction occurs through an (S1/S0)CI conical intersection.
NASA Astrophysics Data System (ADS)
Duan, Yabo; Song, Chengtian
2016-12-01
Empirical mode decomposition (EMD) is a recently proposed nonlinear and nonstationary laser signal denoising method. A noisy signal is broken down using EMD into oscillatory components that are called intrinsic mode functions (IMFs). Thresholding-based denoising and correlation-based partial reconstruction of IMFs are the two main research directions for EMD-based denoising. Similar to other decomposition-based denoising approaches, EMD-based denoising methods require a reliable threshold to determine which IMFs are noise components and which IMFs are noise-free components. In this work, we propose a new approach in which each IMF is first denoised using EMD interval thresholding (EMD-IT), and then a robust thresholding process based on Spearman correlation coefficient is used for relevant modes selection. The proposed method tackles the problem using a thresholding-based denoising approach coupled with partial reconstruction of the relevant IMFs. Other traditional denoising methods, including correlation-based EMD partial reconstruction (EMD-Correlation), discrete Fourier transform and wavelet-based methods, are investigated to provide a comparison with the proposed technique. Simulation and test results demonstrate the superior performance of the proposed method when compared with the other methods.
Payán, Denise D; Sloane, David C; Illum, Jacqueline; Vargas, Roberto B; Lee, Donzella; Galloway-Gilliam, Lark; Lewis, LaVonna B
2017-07-01
This study is a process evaluation of a clinical-community partnership that implemented evidence-based interventions in clinical safety net settings. Adoption and implementation of evidence-based interventions in these settings can help reduce health disparities by improving the quality of clinical preventive services in health care settings with underserved populations. A clinical-community partnership model is a possible avenue to catalyze adoption and implementation of interventions amid organizational barriers to change. Three Federally Qualified Health Centers in South Los Angeles participated in a partnership led by a local community-based organization (CBO) to implement hypertension interventions. Qualitative research methods were used to evaluate intervention selection and implementation processes between January 2014 and June 2015. Data collection tools included a key participant interview guide, health care provider interview guide, and protocol for taking meeting minutes. This case study demonstrates how a CBO acted as an external facilitator and employed a collaborative partnership model to catalyze implementation of evidence-based interventions in safety net settings. The study phases observed included initiation, planning, and implementation. Three emergent categories of organizational facilitators and barriers were identified (personnel capacity, professional development capacity, and technological capacity). Key participants and health care providers expressed a high level of satisfaction with the collaborative and the interventions, respectively. The CBO's role as a facilitator and catalyst is a replicable model to promote intervention adoption and implementation in safety net settings. Key lessons learned are provided for researchers and practitioners interested in partnering with Federally Qualified Health Centers to implement health promotion interventions.
Chao, T.T.; Sanzolone, R.F.
1992-01-01
Sample decomposition is a fundamental and integral step in the procedure of geochemical analysis. It is often the limiting factor to sample throughput, especially with the recent application of the fast and modern multi-element measurement instrumentation. The complexity of geological materials makes it necessary to choose the sample decomposition technique that is compatible with the specific objective of the analysis. When selecting a decomposition technique, consideration should be given to the chemical and mineralogical characteristics of the sample, elements to be determined, precision and accuracy requirements, sample throughput, technical capability of personnel, and time constraints. This paper addresses these concerns and discusses the attributes and limitations of many techniques of sample decomposition along with examples of their application to geochemical analysis. The chemical properties of reagents as to their function as decomposition agents are also reviewed. The section on acid dissolution techniques addresses the various inorganic acids that are used individually or in combination in both open and closed systems. Fluxes used in sample fusion are discussed. The promising microwave-oven technology and the emerging field of automation are also examined. A section on applications highlights the use of decomposition techniques for the determination of Au, platinum group elements (PGEs), Hg, U, hydride-forming elements, rare earth elements (REEs), and multi-elements in geological materials. Partial dissolution techniques used for geochemical exploration which have been treated in detail elsewhere are not discussed here; nor are fire-assaying for noble metals and decomposition techniques for X-ray fluorescence or nuclear methods be discussed. ?? 1992.
Dominant modal decomposition method
NASA Astrophysics Data System (ADS)
Dombovari, Zoltan
2017-03-01
The paper deals with the automatic decomposition of experimental frequency response functions (FRF's) of mechanical structures. The decomposition of FRF's is based on the Green function representation of free vibratory systems. After the determination of the impulse dynamic subspace, the system matrix is formulated and the poles are calculated directly. By means of the corresponding eigenvectors, the contribution of each element of the impulse dynamic subspace is determined and the sufficient decomposition of the corresponding FRF is carried out. With the presented dominant modal decomposition (DMD) method, the mode shapes, the modal participation vectors and the modal scaling factors are identified using the decomposed FRF's. Analytical example is presented along with experimental case studies taken from machine tool industry.
Fichtner, S; Hofmann, J; Möller, A; Schrage, C; Giebelhausen, J M; Böhringer, B; Gläser, R
2013-11-15
For the decomposition of chemical warfare agents, a hybrid material concept was applied. This consists of a copper oxide-containing phase as a component with reactive functionality supported on polymer-based spherical activated carbon (PBSAC) as a component with adsorptive functionality. A corresponding hybrid material was prepared by impregnation of PBSAC with copper(II)nitrate and subsequent calcination at 673K. The copper phase exists predominantly as copper(I)oxide which is homogeneously distributed over the PBSAC particles. The hybrid material containing 16 wt.% copper on PBSAC is capable of self-detoxifying the mustard gas surrogate 2-chloroethylethylsulfide (CEES) at room temperature. The decomposition is related to the breakthrough behavior of the reactant CEES, which displaces the reaction product ethylvinylsulfide (EVS). This leads to a combined breakthrough of CEES and EVS. The decomposition of CEES is shown to occur catalytically over the copper-containing PBSAC material. Thus, the hybrid material can even be considered to be self-cleaning. Copyright © 2013 Elsevier B.V. All rights reserved.
Catalytic decomposition of H2O2 over Fe-based catalysts for simultaneous removal of NOX and SO2
NASA Astrophysics Data System (ADS)
Huang, Xianming; Ding, Jie; Zhong, Qin
2015-01-01
Simultaneous flue gas desulfurization and denitrification were achieved with rad OH radicals from the decomposition of H2O2 over hematite (Fe) as well as hematite supported on alumina (Fe-Al) and anatase (Fe-Ti). Under all conditions, SO2 achieved 100% removal, whereas NOX removal varies with the catalysts. The supporting of Fe over aluminum enhances the catalytic removal of NOX, whereas that of anatase presents negative effect. The NOX removal is determined by the decomposition rate of H2O2 into rad OH radicals over sbnd OH bonded with Fe (Fe-OH). The supporting of Fe over alumina enhances the content of Fe-OH and the points of zero charge (PZC) values, which are beneficial for the production of rad OH radicals. The supporting of Fe over anatase results in the formation of FeOTi, which cannot decompose H2O2 into rad OH radicals. Furthermore, H2O2 tends more to be reacted with TiOH to produce O2 over Fe-Ti. Finally, the enhancement mechanism of H2O2 decomposition over Fe-based catalysts is speculated. It has a contribution to the correct choice for supports and active ingredients of the catalyst in the future industrial applications.
Bains, William; Xiao, Yao; Yu, Changyong
2015-01-01
The components of life must survive in a cell long enough to perform their function in that cell. Because the rate of attack by water increases with temperature, we can, in principle, predict a maximum temperature above which an active terrestrial metabolism cannot function by analysis of the decomposition rates of the components of life, and comparison of those rates with the metabolites’ minimum metabolic half-lives. The present study is a first step in this direction, providing an analytical framework and method, and analyzing the stability of 63 small molecule metabolites based on literature data. Assuming that attack by water follows a first order rate equation, we extracted decomposition rate constants from literature data and estimated their statistical reliability. The resulting rate equations were then used to give a measure of confidence in the half-life of the metabolite concerned at different temperatures. There is little reliable data on metabolite decomposition or hydrolysis rates in the literature, the data is mostly confined to a small number of classes of chemicals, and the data available are sometimes mutually contradictory because of varying reaction conditions. However, a preliminary analysis suggests that terrestrial biochemistry is limited to environments below ~150–180 °C. We comment briefly on why pressure is likely to have a small effect on this. PMID:25821932
L. M. Petkovic; D. M. Ginosar; H. W. Rollins; K. C. Burch; P. J. Pinhero; H. H. Farrell
2008-04-01
Thermochemical cycles consist of a series of chemical reactions to produce hydrogen from water at lower temperatures than by direct thermal decomposition. All the sulfur-based cycles for water splitting employ the sulfuric acid decomposition reaction. This work reports the studies performed on platinum supported on titania (rutile) catalysts to investigate the causes of catalyst deactivation under sulfuric acid decomposition reaction conditions. Samples of 1 wt% Pt/TiO2 (rutile) catalysts were submitted to flowing concentrated sulfuric acid at 1123 K and atmospheric pressure for different times on stream (TOS) between 0 and 548 h. Post-operation analyses of the spent catalyst samples showed that Pt oxidation and sintering occurred under reaction conditions and some Pt was lost by volatilization. Pt loss rate was higher at initial times but total loss appeared to be independent of the gaseous environment. Catalyst activity showed an initial decrease that lasted for about 66 h, followed by a slight recovery of activity between 66 and 102 h TOS, and a period of slower deactivation after 102 h TOS. Catalyst sulfation did not seem to be detrimental to catalyst activity and the activity profile suggested that a complex dynamical situation involving platinum sintering, volatilization, and oxidation, along with TiO2 morphological changes affected catalyst activity in a non-monotonic way.
Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang
2013-01-01
China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model–panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity. PMID:24353753
Dong, Feng; Long, Ruyin; Chen, Hong; Li, Xiaohui; Yang, Qingliang
2013-01-01
China is considered to be the main carbon producer in the world. The per-capita carbon emissions indicator is an important measure of the regional carbon emissions situation. This study used the LMDI factor decomposition model-panel co-integration test two-step method to analyze the factors that affect per-capita carbon emissions. The main results are as follows. (1) During 1997, Eastern China, Central China, and Western China ranked first, second, and third in the per-capita carbon emissions, while in 2009 the pecking order changed to Eastern China, Western China, and Central China. (2) According to the LMDI decomposition results, the key driver boosting the per-capita carbon emissions in the three economic regions of China between 1997 and 2009 was economic development, and the energy efficiency was much greater than the energy structure after considering their effect on restraining increased per-capita carbon emissions. (3) Based on the decomposition, the factors that affected per-capita carbon emissions in the panel co-integration test showed that Central China had the best energy structure elasticity in its regional per-capita carbon emissions. Thus, Central China was ranked first for energy efficiency elasticity, while Western China was ranked first for economic development elasticity.
Controllable pneumatic generator based on the catalytic decomposition of hydrogen peroxide
Kim, Kyung-Rok; Kim, Kyung-Soo Kim, Soohyun
2014-07-15
This paper presents a novel compact and controllable pneumatic generator that uses hydrogen peroxide decomposition. A fuel micro-injector using a piston-pump mechanism is devised and tested to control the chemical decomposition rate. By controlling the injection rate, the feedback controller maintains the pressure of the gas reservoir at a desired pressure level. Thermodynamic analysis and experiments are performed to demonstrate the feasibility of the proposed pneumatic generator. Using a prototype of the pneumatic generator, it takes 6 s to reach 3.5 bars with a reservoir volume of 200 ml at the room temperature, which is sufficiently rapid and effective to maintain the repetitive lifting of a 1 kg mass.
Controllable pneumatic generator based on the catalytic decomposition of hydrogen peroxide.
Kim, Kyung-Rok; Kim, Kyung-Soo; Kim, Soohyun
2014-07-01
This paper presents a novel compact and controllable pneumatic generator that uses hydrogen peroxide decomposition. A fuel micro-injector using a piston-pump mechanism is devised and tested to control the chemical decomposition rate. By controlling the injection rate, the feedback controller maintains the pressure of the gas reservoir at a desired pressure level. Thermodynamic analysis and experiments are performed to demonstrate the feasibility of the proposed pneumatic generator. Using a prototype of the pneumatic generator, it takes 6 s to reach 3.5 bars with a reservoir volume of 200 ml at the room temperature, which is sufficiently rapid and effective to maintain the repetitive lifting of a 1 kg mass.
Controllable pneumatic generator based on the catalytic decomposition of hydrogen peroxide
NASA Astrophysics Data System (ADS)
Kim, Kyung-Rok; Kim, Kyung-Soo; Kim, Soohyun
2014-07-01
This paper presents a novel compact and controllable pneumatic generator that uses hydrogen peroxide decomposition. A fuel micro-injector using a piston-pump mechanism is devised and tested to control the chemical decomposition rate. By controlling the injection rate, the feedback controller maintains the pressure of the gas reservoir at a desired pressure level. Thermodynamic analysis and experiments are performed to demonstrate the feasibility of the proposed pneumatic generator. Using a prototype of the pneumatic generator, it takes 6 s to reach 3.5 bars with a reservoir volume of 200 ml at the room temperature, which is sufficiently rapid and effective to maintain the repetitive lifting of a 1 kg mass.
The processing of rotor startup signals based on empirical mode decomposition
NASA Astrophysics Data System (ADS)
Gai, Guanghong
2006-01-01
In this paper, we applied empirical mode decomposition method to analyse rotor startup signals, which are non-stationary and contain a lot of additional information other than that from its stationary running signals. The methodology developed in this paper decomposes the original startup signals into intrinsic oscillation modes or intrinsic modes function (IMFs). Then, we obtained rotating frequency components for Bode diagrams plot by corresponding IMFs, according to the characteristics of rotor system. The method can obtain precise critical speed without complex hardware support. The low-frequency components were extracted from these IMFs in vertical and horizontal directions. Utilising these components, we constructed a drift locus of rotor revolution centre, which provides some significant information to fault diagnosis of rotating machinery. Also, we proved that empirical mode decomposition method is more precise than Fourier filter for the extraction of low-frequency component.
Not Available
1992-05-01
The bibliography contains citations concerning the decomposition of toxic materials by biological means. Bacteria, enzymes, and bioluminescence are among the methods discussed. Bacteria and enzymes that digest toluene, polychlorinated biphenyls (PCBs), selenium wastes, oil shale waste, uranium, oil sludge, pesticides, rubber wastes, and pentachlorophenol are discussed. Flavobacterium and white rot fungus are among the biological agents highlighted. (Contains 250 citations and includes a subject term index and title list.)
The QR-Decomposition Based Least-Squares Lattice Algorithm for Adaptive Filtering
1990-07-01
Copyright © Controller HMSO London 1990 THIS PAGE IS LEFT BLANI( INTENTIONALLY CONTENTS 1. INTRODUCION ...bring together the work of Lewis [9] and McWhiner[ 14]. Lewis began with the standard (covariance domain) multi-channel least squares lattice equations...decomposition. As the bulk of the calculation is exactly the computation of the reflection coefficients. Lewis pmoceeded no further with this re-formu
Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions
Fattebert, J.-L.; Richards, D.F.; Glosli, J.N.
2012-12-01
We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10^{6} particles on 65,536 MPI tasks.
An Efficient Solver of Elasto-plastic Problems in Mechanics Based on TFETI Domain Decomposition
NASA Astrophysics Data System (ADS)
Čermák, M.; Kozubek, T.; Markopoulos, A.
2011-09-01
This paper illustrates how to implement efficiently solvers for elasto-plastic problems. We consider the time step problems formulated by nonlinear variational equations in terms of displacements. To treat nonlinearity and nonsmoothnes we use semismooth Newton method. In each Newton iteration we have to solve linear system of algebraic equations and for its numerical solution we use TFETI domain decomposition method. In our benchmark we demonstrate our approach on von Mises plasticity with isotropic hardening using the return mapping concept.
A Graph Decomposition Technique Based on a High-Density Clustering Model on Graphs.
1980-07-01
ADAO90 3A8 ALFRED P SLOAN SCHOOL OF MANAGEMNT CAMBRIDGE MA CEN-ETC FIG 12 GRAPH DECOMPOSITION TECHNIQUE BASEO ON A HIGH-DENSITY CLUSTER-ETC(U) JUL 0...ELEMENT.’ PROJECT, TASK Center for Information Systems Research AREAO G ORK UNIT NUMBERS Sloan School of Management, M.I.T. V Cambridge,_MA__02139...See Kernighan and Lin (1970), Lukes (1974, 1975), anc Christofides and Brooker (1976) for methods that operate under some size constraints on the
NASA Astrophysics Data System (ADS)
Galperti, C.; Marchetto, C.; Alessi, E.; Minelli, D.; Mosconi, M.; Belli, F.; Boncagni, L.; Botrugno, A.; Buratti, P.; Calabro', G.; Esposito, B.; Garavaglia, S.; Granucci, G.; Grosso, A.; Mellera, V.; Moro, A.; Piergotti, V.; Pucella, G.; Ramogida, G.; Bin, W.; Sozzi, C.
2014-11-01
The biorthogonal decomposition analysis of signals from an array of Mirnov coils is able to provide the spatial structure and the temporal evolution of magnetohydrodynamic (MHD) instabilities in a tokamak. Such analysis can be adapted to a data acquisition and elaboration system suitable for fast real time applications such as instability detection and disruption precursory markers computation. This paper deals with the description of this technique as applied to the Frascati Tokamak Upgrade (FTU).
Dynamic formant extraction of wa language based on adaptive variational mode decomposition
NASA Astrophysics Data System (ADS)
Fu, Meijun; Dong, Huazhen; Pan, Wenlin
2017-08-01
Wa language is one of Chinese minority languages spoken by the Wa nationality who lives in Yunnan Province, China. Until now, it has not been studied from the perspective of Engineering Phonetics. In this paper, for the above reason, by the adaptive variational mode decomposition (AVMD) we have investigated the dynamic formant characteristics of Wa language. Firstly, more precisely, use the synthetic dimension to split Wa language isolated words into voiceless and voiced segment, initials and finals. Secondly, use Linear Prediction Coding to estimate the first three formant frequencies and their bandwidths roughly. Thirdly, select the appropriate equilibrium constraint parameter and the number of decomposed layers so that Adaptive Variational Mode Decomposition (AVMD) can decompose the signal into some intrinsic mode functions (IMFs) without pattern aliasing. Fourthly, use the estimated formant frequencies and bandwidths to determine precisely the required IMFs. Fifthly, use the Hilbert transform to calculate the instantaneous frequency of the above determinate IMFs. Further, we implement the weight average operation on instantaneous frequencies to obtain the first three formant frequencies for each frame. Finally, comparing the first three formant frequencies obtained by the adaptive variance modal decomposition and by Praat software respectively, so we have drawn the conclusion that the relative correct rate of the former to the latter can reach 86% averagely in terms of the selected isolated words, which has shown that our method is effective on Wa language.
Huang, Shaoguang; Tian, Lan; Ma, Xiaojie; Wei, Ying
2016-04-01
Hearing impaired people have their own hearing loss characteristics and listening preferences. Therefore hearing aid system should become more natural, humanized and personalized, which requires the filterbank in hearing aids provides flexible sound wave decomposition schemes, so that patients are likely to use the most suitable scheme for their own hearing compensation strategy. In this paper, a reconfigurable sound wave decomposition filterbank is proposed. The prototype filter is first cosine modulated to generate uniform subbands. Then by non-linear transformation the uniform subbands are mapped to nonuniform subbands. By changing the control parameters, the nonlinear transformation changes which leads to different subbands allocations. It provides four different sound wave decomposition schemes without changing the structure of the filterbank. The performance of the proposed reconfigurable filterbank was compared with that of fixed filerbanks, fully customizable filterbanks and other existing reconfigurable filterbanks. It is shown that the proposed filterbank provides satisfactory matching performance as well as low complexity and delay, which make it suitable for real hearing aid applications.
Pan, Kuan Lun; Chen, Mei Chung; Yu, Sheng Jen; Yan, Shaw Yi; Chang, Moo Been
2016-06-01
Direct decompositions of nitric oxide (NO) by La0.7Ce0.3SrNiO4, La0.4Ba0.4Ce0.2SrNiO4, and Pr0.4Ba0.4Ce0.2SrNiO4 are experimentally investigated, and the catalysts are tested with different operating parameters to evaluate their activities. Experimental results indicate that the physical and chemical properties of La0.7Ce0.3SrNiO4 are significantly improved by doping with Ba and partial substitution with Pr. NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4 are 32% and 68%, respectively, at 400 °C with He as carrier gas. As the temperature is increased to 600 °C, NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4, respectively, reach 100% with the inlet NO concentration of 1000 ppm while the space velocity is fixed at 8000 hr(-1). Effects of O2, H2O(g), and CO2 contents and space velocity on NO decomposition are also explored. The results indicate that NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4, respectively, are slightly reduced as space velocity is increased from 8000 to 20,000 hr(-1) at 500 °C. In addition, the activities of both catalysts (La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4) for NO decomposition are slightly reduced in the presence of 5% O2, 5% CO2, or 5% H2O(g). For durability test, with the space velocity of 8000 hr(-1) and operating temperature of 600 °C, high N2 yield is maintained throughout the durability test of 60 hr, revealing the long-term stability of Pr0.4Ba0.4Ce0.2SrNiO4 for NO decomposition. Overall, Pr0.4Ba0.4Ce0.2SrNiO4 shows good catalytic activity for NO decomposition. Nitrous oxide (NO) not only causes adverse environmental effects such as acid rain, photochemical smog, and deterioration of visibility and water quality, but also harms human lungs and respiratory system. Pervoskite-type catalysts, including La0.7Ce0.3SrNiO4, La0.4Ba0.4Ce0.2SrNiO4, and Pr0.4Ba0.4Ce0.2SrNiO4, are applied for direct
Kök, Gökhan; Ay, Kadir; Ay, Emriye; Doğan, Fatih; Kaya, Ismet
2014-01-30
A glycopolymer, poly(3-O-methacroyl-5,6-O-isopropylidene-1,2-O-(S)-trichloroethylidene-α-d-galactofuranose) (PMIPTEG) was synthesized from the sugar-carrying methacrylate monomer, 3-O-methacroyl-5,6-O-isopropylidene-1,2-O-(S)-trichloroethylidene-α-d-galactofuranose (MIPTEG) via conventional free radical polymerization with AIBN in 1,4-dioxane. The structures of glycomonomer and their polymers were confirmed by UV-vis, FT-IR, (1)H NMR, (13)C NMR, GPC, TG/DTG-DTA, DSC, and SEM techniques. SEM images showed that PMIPTEG had a straight-chain length structure. On the other hand, the thermal decomposition kinetics of polymer were investigated by means of thermogravimetric analysis in dynamic nitrogen atmosphere at different heating rates. The apparent activation energies for thermal decomposition of the PMIPTEG were calculated using the Kissinger, Kim-Park, Tang, Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS) and Friedman methods and were found to be 100.15, 104.40, 102.0, 102.2, 103.2 and 99.6 kJ/mol, respectively. The most likely process mechanism related to the thermal decomposition stage of PMIPTEG was determined to be a Dn deceleration type in terms of master plots results.
Lauridsen, Vibeke H; Ibsen, Lise; Blom, Jakob; Jørgensen, Karl Anker
2016-03-01
Conjugated cyclic trienes have the potential for different types of cycloaddition reactions. In the present work, we will, in a novel asymmetric cycloaddition reaction, demonstrate that the organocatalytic reaction of 2-acyl cycloheptatrienes with azomethine ylides proceeds as a [3+2] cycloaddition, which is in contrast to the Lewis acid-catalyzed reaction, in which a [3+6] cycloaddition takes place. In the presence of a chiral organosuperbase, 2-acyl cycloheptatrienes react in a highly enantioselective manner in the [3+2] cycloaddition with azomethine ylides, providing the 1,3-dipolar cycloaddition product in high yields and up to 99 % ee. It is also shown that the diene formed by the reaction can undergo stereoselective dihydroxylation, bromination, and cycloaddition reactions. Finally, based on experimental observations, some mechanistic considerations are discussed.
Dzhemilev, U.M.; Selimov, F.A.; Khafizov, V.R.
1987-01-20
It has been shown that ..cap alpha..,omega-nitrileacetylenes under the action of homogeneous cobalt-containing catalysts undergo transformations into pyridine derivatives. In order to expand the scope of this method for synthesis of complex pyridine bases, for investigation of the reactivity of nitrileacetylenes of various structure in the reaction of cooligomerization with acetylene, as well as for the introduction to these reactions of new types of ..cap alpha..,omega-nitrileacetylenes, containing in their molecules an oxygen atom, they studied the homo- and codimerization of ..cap alpha..,omega-nitrileacetylenes with acetylene under the action of a Co(2-ethyl hexanoate)/sub 2/-AIR/sub 3/ catalyst in a toluene solution. Cyclodimerization of acetylene with ..cap alpha..,omega-nitrileacetylenes, catalyzed by a Co(2-ethyl hexanoate)/sub 2/-AlEt/sub 3/ system gives new types of mono- and bicyclic pyridines.
Chiu, Chun-Huo; Chao, Anne
2014-01-01
Hill numbers (or the "effective number of species") are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify "the effective number of equally abundant and (functionally) equally distinct species" in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of the
Chiu, Chun-Huo; Chao, Anne
2014-01-01
Hill numbers (or the “effective number of species”) are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify “the effective number of equally abundant and (functionally) equally distinct species” in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of
Effect of Palladium Form on Tetraphenylborate Decomposition Rate
Walker, D.D.
1998-04-28
Palladium catalyzes the decomposition of tetraphenylborate in alkaline solutions. Researchers postulate several decomposition mechanisms that differ in the form of the palladium catalyst. Potential forms include solid and soluble, different soluble species (such as aqueous or organic soluble), and different oxidation states (i.e., 0, II, and IV). Initial tests measured the reactivity and distribution of four Pd forms in tetraphenylborate slurries.
Contaminated Groundwater Remediation by Catalyzed Hydrogen Peroxide and Persulfate Oxidants System
NASA Astrophysics Data System (ADS)
Yan, N.; Wang, Y.; Brusseau, M. L.
2014-12-01
A binary oxidant system, catalyzed hydrogen peroxide (H2O2) coupled with persulfate (S2O82-), was investigated for use in in-situ chemical oxidation (ISCO) applications. Trichloroethene (TCE) and 1,4-dioxane were used as target contaminants. Batch experiments were conducted to investigate the catalytic efficiency between ferrous ion (Fe2+) and base (NaOH), oxidant decomposition rates, and contaminant degradation efficiency. For the base-catalyzed H2O2-S2O82- system, oxidant release was moderate and sustained over the entire test period of 96 hours. Conversely, the oxidants were depleted within 24 hours for the Fe2+-catalyzed system. Solution pH decreased slightly for the Fe2+-catalyzed system, whereas the pH increased for the base-catalyzed system. The rates of degradation for TCE and 1,4-dioxane are compared as a function of system conditions. The results of this study indicate that the binary H2O2-S2O82- oxidant system is effective for oxidation of the tested contaminants.
Liu, Leili; Li, Jie; Zhang, Lingyao; Tian, Siyu
2017-08-24
MgH2, Mg2NiH4, and Mg2CuH3 were prepared, and their structure and hydrogen storage properties were determined through X-ray photoelectron spectroscopy and thermal analyzer. The effects of MgH2, Mg2NiH4, and Mg2CuH3 on the thermal decomposition, burning rate, and explosive heat of ammonium perchlorate-based composite solid propellant were subsequently studied. Results indicated that MgH2, Mg2NiH4, and Mg2CuH3 can decrease the thermal decomposition peak temperature and increase the total released heat of decomposition. These compounds can improve the effect of thermal decomposition of the propellant. The burning rates of the propellant increased using Mg-based hydrogen storage materials as promoter. The burning rates of the propellant also increased using MgH2 instead of Al in the propellant, but its explosive heat was not enlarged. Nonetheless, the combustion heat of MgH2 was higher than that of Al. A possible mechanism was thus proposed. Copyright © 2017. Published by Elsevier B.V.
Prediction of oxidoreductase-catalyzed reactions based on atomic properties of metabolites.
Mu, Fangping; Unkefer, Pat J; Unkefer, Clifford J; Hlavacek, William S
2006-12-15
Our knowledge of metabolism is far from complete, and the gaps in our knowledge are being revealed by metabolomic detection of small-molecules not previously known to exist in cells. An important challenge is to determine the reactions in which these compounds participate, which can lead to the identification of gene products responsible for novel metabolic pathways. To address this challenge, we investigate how machine learning can be used to predict potential substrates and products of oxidoreductase-catalyzed reactions. We examined 1956 oxidation/reduction reactions in the KEGG database. The vast majority of these reactions (1626) can be divided into 12 subclasses, each of which is marked by a particular type of functional group transformation. For a given transformation, the local structures of reaction centers in substrates and products can be characterized by patterns. These patterns are not unique to reactants but are widely distributed among KEGG metabolites. To distinguish reactants from non-reactants, we trained classifiers (linear-kernel Support Vector Machines) using negative and positive examples. The input to a classifier is a set of atomic features that can be determined from the 2D chemical structure of a compound. Depending on the subclass of reaction, the accuracy of prediction for positives (negatives) is 64 to 93% (44 to 92%) when asking if a compound is a substrate and 71 to 98% (50 to 92%) when asking if a compound is a product. Sensitivity analysis reveals that this performance is robust to variations of the training data. Our results suggest that metabolic connectivity can be predicted with reasonable accuracy from the presence or absence of local structural motifs in compounds and their readily calculated atomic features. Classifiers reported here can be used freely for noncommercial purposes via a Java program available upon request.
Chen, Xin; Ge, Fei-Fei; Lu, Tao; Zhou, Qing-Fa
2015-03-20
Highly stereoselective intermolecular reactions of electron-deficient alkynes with N-hydroxyphthalimides for efficient construction of N-unprotected 3-methyleneisoindolin-1-ones have been developed through base catalytic strategies. The reaction of alkynoates with N-hydroxyphthalimides catalyzed by Bu3P in DMF at 150 °C gave the corresponding 3-methyleneisoindolin-1-ones with a (Z)-configuration, while the reaction of alkynoates with N-hydroxyphthalimides catalyzed by K2CO3 in DMF at 60 °C gave the corresponding 3-methyleneisoindolin-1-ones with an (E)-configuration, and (Z)-3-methyleneisoindolin-1-ones were obtained when alkyne ketones reacted with N-hydroxyphthalimide.
Gnamm, Christian; Brödner, Kerstin; Krauter, Caroline M; Helmchen, Günter
2009-10-12
A method for the stereoselective synthesis of 2,6-disubstituted piperidines has been developed that is based on the use of an intramolecular iridium-catalyzed allylic substitution as a configurational switch. The procedure allows the preparation of 2-vinylpiperidines with enantiomeric excesses (ee) of greater than 99%. As applications, total syntheses of piperidine alkaloids have been elaborated, most often by using Ru-catalyzed cross-metatheses as a key step for introduction of a side chain. Asymmetric total syntheses of the prosopis alkaloids (+)-prosopinine, (+)-prosophylline, (+)-prosopine, and of the dendrobate alkaloid (+)-241D and its C6 epimer are described.
Guo, Qiang; Qi, Liangang
2017-01-01
In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal. PMID:28394290
Zhang, Xiaoxing; Huang, Rong; Gui, Yingang; Zeng, Hong
2016-11-01
Detection of decomposition products of sulfur hexafluoride (SF₆) is one of the best ways to diagnose early latent insulation faults in gas-insulated equipment, and the occurrence of sudden accidents can be avoided effectively by finding early latent faults. Recently, functionalized graphene, a kind of gas sensing material, has been reported to show good application prospects in the gas sensor field. Therefore, calculations were performed to analyze the gas sensing properties of intrinsic graphene (Int-graphene) and functionalized graphene-based material, Ag-decorated graphene (Ag-graphene), for decomposition products of SF₆, including SO₂F₂, SOF₂, and SO₂, based on density functional theory (DFT). We thoroughly investigated a series of parameters presenting gas-sensing properties of adsorbing process about gas molecule (SO₂F₂, SOF₂, SO₂) and double gas molecules (2SO₂F₂, 2SOF₂, 2SO₂) on Ag-graphene, including adsorption energy, net charge transfer, electronic state density, and the highest and lowest unoccupied molecular orbital. The results showed that the Ag atom significantly enhances the electrochemical reactivity of graphene, reflected in the change of conductivity during the adsorption process. SO₂F₂ and SO₂ gas molecules on Ag-graphene presented chemisorption, and the adsorption strength was SO₂F₂ > SO₂, while SOF₂ absorption on Ag-graphene was physical adsorption. Thus, we concluded that Ag-graphene showed good selectivity and high sensitivity to SO₂F₂. The results can provide a helpful guide in exploring Ag-graphene material in experiments for monitoring the insulation status of SF₆-insulated equipment based on detecting decomposition products of SF₆.
Guo, Qiang; Qi, Liangang
2017-04-10
In the coexistence of multiple types of interfering signals, the performance of interference suppression methods based on time and frequency domains is degraded seriously, and the technique using an antenna array requires a large enough size and huge hardware costs. To combat multi-type interferences better for GNSS receivers, this paper proposes a cascaded multi-type interferences mitigation method combining improved double chain quantum genetic matching pursuit (DCQGMP)-based sparse decomposition and an MPDR beamformer. The key idea behind the proposed method is that the multiple types of interfering signals can be excised by taking advantage of their sparse features in different domains. In the first stage, the single-tone (multi-tone) and linear chirp interfering signals are canceled by sparse decomposition according to their sparsity in the over-complete dictionary. In order to improve the timeliness of matching pursuit (MP)-based sparse decomposition, a DCQGMP is introduced by combining an improved double chain quantum genetic algorithm (DCQGA) and the MP algorithm, and the DCQGMP algorithm is extended to handle the multi-channel signals according to the correlation among the signals in different channels. In the second stage, the minimum power distortionless response (MPDR) beamformer is utilized to nullify the residuary interferences (e.g., wideband Gaussian noise interferences). Several simulation results show that the proposed method can not only improve the interference mitigation degree of freedom (DoF) of the array antenna, but also effectively deal with the interference arriving from the same direction with the GNSS signal, which can be sparse represented in the over-complete dictionary. Moreover, it does not bring serious distortions into the navigation signal.
Keith, Jeff; Westbury, Chris; Goldman, James
2015-09-01
Corpus-based semantic space models, which primarily rely on lexical co-occurrence statistics, have proven effective in modeling and predicting human behavior in a number of experimental paradigms that explore semantic memory representation. The most widely studied extant models, however, are strongly influenced by orthographic word frequency (e.g., Shaoul & Westbury, Behavior Research Methods, 38, 190-195, 2006). This has the implication that high-frequency closed-class words can potentially bias co-occurrence statistics. Because these closed-class words are purported to carry primarily syntactic, rather than semantic, information, the performance of corpus-based semantic space models may be improved by excluding closed-class words (using stop lists) from co-occurrence statistics, while retaining their syntactic information through other means (e.g., part-of-speech tagging and/or affixes from inflected word forms). Additionally, very little work has been done to explore the effect of employing morphological decomposition on the inflected forms of words in corpora prior to compiling co-occurrence statistics, despite (controversial) evidence that humans perform early morphological decomposition in semantic processing. In this study, we explored the impact of these factors on corpus-based semantic space models. From this study, morphological decomposition appears to significantly improve performance in word-word co-occurrence semantic space models, providing some support for the claim that sublexical information-specifically, word morphology-plays a role in lexical semantic processing. An overall decrease in performance was observed in models employing stop lists (e.g., excluding closed-class words). Furthermore, we found some evidence that weakens the claim that closed-class words supply primarily syntactic information in word-word co-occurrence semantic space models.
Zhang, Xiaoxing; Huang, Rong; Gui, Yingang; Zeng, Hong
2016-01-01
Detection of decomposition products of sulfur hexafluoride (SF6) is one of the best ways to diagnose early latent insulation faults in gas-insulated equipment, and the occurrence of sudden accidents can be avoided effectively by finding early latent faults. Recently, functionalized graphene, a kind of gas sensing material, has been reported to show good application prospects in the gas sensor field. Therefore, calculations were performed to analyze the gas sensing properties of intrinsic graphene (Int-graphene) and functionalized graphene-based material, Ag-decorated graphene (Ag-graphene), for decomposition products of SF6, including SO2F2, SOF2, and SO2, based on density functional theory (DFT). We thoroughly investigated a series of parameters presenting gas-sensing properties of adsorbing process about gas molecule (SO2F2, SOF2, SO2) and double gas molecules (2SO2F2, 2SOF2, 2SO2) on Ag-graphene, including adsorption energy, net charge transfer, electronic state density, and the highest and lowest unoccupied molecular orbital. The results showed that the Ag atom significantly enhances the electrochemical reactivity of graphene, reflected in the change of conductivity during the adsorption process. SO2F2 and SO2 gas molecules on Ag-graphene presented chemisorption, and the adsorption strength was SO2F2 > SO2, while SOF2 absorption on Ag-graphene was physical adsorption. Thus, we concluded that Ag-graphene showed good selectivity and high sensitivity to SO2F2. The results can provide a helpful guide in exploring Ag-graphene material in experiments for monitoring the insulation status of SF6-insulated equipment based on detecting decomposition products of SF6. PMID:27809269
Powers, V.M.; Koo, C.W.; Kenyon, G.L. ); Gerlt, J.A.; Kozarich, J.W. )
1991-09-24
The fate of the {alpha}-hydrogen of mandelate in the reaction catalyzed by mandelate racemase has been investigated by a mass spectroscopic method. The method entails the incubation of (R)- or (S)-({alpha}-{sup 1}H) mandelate in buffered D{sub 2}O to a low extent of turnover (about 5-8%), esterification of the resulting mixture of mandelates with diazomethane, derivatization of the methyl esters with a chiral derivatizing agent, and quantitation of the isotope content of the {alpha}-hydrogen of both substrate and product by gas chromatography/mass spectrometric analysis. No significant substrate-derived {alpha}-protium was found in the product for racemization in either direction. In addition, in the (R) to (S) direction almost no exchange of the {alpha}-hydrogen in the remaining (R) substrate pool occurred, but in the (S) to (R) direction 3.5-5.1% exchange of the {alpha}-hydrogen in the remaining substrate (after 5.1-7.2% net turnover) was found. Qualitatively similar results were obtained in the (S) to (R) direction in H{sub 2}O when (S)-({alpha}-{sup 2}H)mandelate was used as substrate. In other experiments, an overshoot in the progress curve was observed when the racemization of either enantiomer of ({alpha}-{sup 1}H) mandelate in D{sub 2}O was monitored by following the change in ellipticity of the reaction mixture; the magnitude of the overshoot was greater in the (R) to (S) than in the (S) to (R) direction. All of the available data indicate that the reaction catalyzed by mandelate racemase proceeds by a two-base mechanism, in contrast to earlier proposals.
Bizopoulos, Paschalis A; Al-Ani, Tarik; Tsalikakis, Dimitrios G; Tzallas, Alexandros T; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I
2013-01-01
Electrooculographic (EOG) artefacts are one of the most common causes of Electroencephalogram (EEG) distortion. In this paper, we propose a method for EOG Blinking Artefacts (BAs) detection and removal from EEG. Normalized Correlation Coefficient (NCC), based on a predetermined BA template library was used for detecting the BA. Ensemble Empirical Mode Decomposition (EEMD) was applied to the contaminated region and a statistical algorithm determined which Intrinsic Mode Functions (IMFs) correspond to the BA. The proposed method was applied in simulated EEG signals, which were contaminated with artificially created EOG BAs, increasing the Signal-to-Error Ratio (SER) of the EEG Contaminated Region (CR) by 35 dB on average.
NASA Astrophysics Data System (ADS)
Kim, Sung Yong
2016-04-01
This paper presents a data-derived surface current forecast model based on statistical decomposition techniques [Kim et al 2010] on the observations of high-frequency radar-derived surface currents, local winds, and sea surface height anomalies (SSHA) off southern San Diego. The regional surface circulation mainly consists of tide-, wind-, and low-frequency pressure gradient-coherent components, which leads us to use tidal harmonic analysis, response functions using wind stress and pressure gradients, autoregressive analysis for residual components in the forecast model. These basis functions have been consecutively added, and the performance of corresponding forecast models is evaluated.
Men, Kuo; Quan, Hong; Yang, Peipei; Cao, Ting; Li, Weihao
2010-04-01
The frequency-domain magnetic resonance spectroscopy (MRS) is achieved by the Fast Fourier Transform (FFT) of the time-domain signals. Usually we are only interested in the portion lying in a frequency band of the whole spectrum. A method based on the singular value decomposition (SVD) and frequency-selection is presented in this article. The method quantifies the spectrum lying in the interested frequency band and reduces the interference of the parts lying out of the band in a computationally efficient way. Comparative experiments with the standard time-domain SVD method indicate that the method introduced in this article is accurate and timesaving in practical situations.
Study of SF6 gas decomposition products based on spectroscopy technology
NASA Astrophysics Data System (ADS)
Cai, Ji-xing; Na, Yan-xiang; Ni, Wei-yuan; Li, Guo-wei; Feng, Ke-cheng; Song, Gui-cai
2011-08-01
With the rapid development of power industry, the number of SF6 electrical equipment are increasing, it has gradually replaced the traditional insulating oil material as insulation and arc media in the high-voltage electrical equipment. Pure SF6 gas has excellent insulating properties and arc characteristics; however, under the effect of the strong arc, SF6 gas will decompose and generate toxic substances, then corroding electrical equipment, thereby affecting the insulation and arc ability of electrical equipment. If excessive levels of impurities in the gas that will seriously affect the mechanical properties, breaking performance and electrical performance of electrical equipment, it will cause many serious consequences, even threaten the safe operation of the grid. This paper main analyzes the basic properties of SF6 gas and the basic situation of decomposition in the discharge conditions, in order to simulate the actual high-voltage electrical equipment, designed and produced a simulation device that can simulate the decomposition of SF6 gas under a high voltage discharge, and using fourier transform infrared spectroscopy to analyze the sample that produced by the simulation device. The result show that the main discharge decomposition product is SO2F2 (sulfuryl fluoride), the substance can react with water and generate corrosive H2SO4(sulfuric acid) and HF (hydrogen fluoride), also found that the increase in the number with the discharge, SO2F2concentration levels are on the rise. Therefore, the material can be used as one of the main characteristic gases to determine the SF6 electrical equipment failure, and to monitor their concentration levels.
ERIC Educational Resources Information Center
Napier, J.
1988-01-01
Outlines the role of the main organisms involved in woodland decomposition and discusses some of the variables affecting the rate of nutrient cycling. Suggests practical work that may be of value to high school students either as standard practice or long-term projects. (CW)
ERIC Educational Resources Information Center
Napier, J.
1988-01-01
Outlines the role of the main organisms involved in woodland decomposition and discusses some of the variables affecting the rate of nutrient cycling. Suggests practical work that may be of value to high school students either as standard practice or long-term projects. (CW)
NASA Astrophysics Data System (ADS)
Higham, J. E.; Brevis, W.; Keylock, C. J.
2016-12-01
The present work proposes a novel method of detection and estimation of outliers in particle image velocimetry measurements by the modification of the temporal coefficients associated with a proper orthogonal decomposition of an experimental time series. Using synthetic outliers applied to two sequences of vector fields, the method is benchmarked against state-of-the-art approaches recently proposed to remove the influence of outliers. Compared with these methods, the proposed approach offers an increase in accuracy and robustness for the detection of outliers and comparable accuracy for their estimation.
Dynamics of a fractional-order simplified unified system based on the Adomian decomposition method
NASA Astrophysics Data System (ADS)
Xu, Yixin; Sun, Kehui; He, Shaobo; Zhang, Limin
2016-06-01
In this paper, the Adomian decomposition method (ADM) is applied to solve the fractional-order simplified unified system. The dynamics of the system is analyzed by means of the Lyapunov exponent spectrum, bifurcations, chaotic attractor, power spectrum and maximum Lyapunov exponent diagram. Route to chaos by period doubling is observed. Chaos is found to exist in the system with order as low as 1.371. In addition, chaotic behaviors are studied with different dimensional order, and the results show that this system is chaotic when only the first or third dimension is fractional.
NASA Astrophysics Data System (ADS)
Chen, Hang; Tanougast, Camel; Liu, Zhengjun; Sieler, Loic
2017-06-01
An enhanced asymmetric cryptosystem for color image is proposed by using equal modulus decomposition (EMD) in the gyrator transform domains. In this scheme, the EMD is performed to create the effective trapdoor one-way function. Moreover, to enhance the security of the cryptosystem, the Baker mapping is considered and utilized for scrambling the RGB components of the color image. The parameters in the Baker mapping and gyrator transform can be served as the extra keys of the entire cryptosystem. Various types of attacks are considered in the robustness analysis experiments. Some numerical simulations are made to verify the validity and capability of the proposed color encryption algorithm.
Thermal decomposition of magnesium and calcium sulfates
Roche, S L
1982-04-01
The effect of catalyst on the thermal decomposition of MgSO/sub 4/ and CaSO/sub 4/ in vacuum was studied as a function of time in Knudsen cells and for MgSO/sub 4/, in open crucibles in vacuum in a Thermal Gravimetric Apparatus. Platinum and Fe/sub 2/O/sub 3/ were used as catalysts. The CaSO/sub 4/ decomposition rate was approximately doubled when Fe/sub 2/O/sub 3/ was present in a Knudsen cell. Platinum did not catalyze the CaSO/sub 4/ decomposition reaction. The initial decomposition rate for MgSO/sub 4/ was approximately 5 times greater than when additives were present in Knudsen cells but only about 1.5 times greater when decomposition was done in an open crucible.
Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy
Hünemohr, Nora Greilich, Steffen; Paganetti, Harald; Seco, Joao; Jäkel, Oliver
2014-06-15
Purpose: The authors describe a novel method of predicting mass density and elemental mass fractions of tissues from dual energy CT (DECT) data for Monte Carlo (MC) based dose planning. Methods: The relative electron density ϱ{sub e} and effective atomic number Z{sub eff} are calculated for 71 tabulated tissue compositions. For MC simulations, the mass density is derived via one linear fit in the ϱ{sub e} that covers the entire range of tissue compositions (except lung tissue). Elemental mass fractions are predicted from the ϱ{sub e} and the Z{sub eff} in combination. Since particle therapy dose planning and verification is especially sensitive to accurate material assignment, differences to the ground truth are further analyzed for mass density, I-value predictions, and stopping power ratios (SPR) for ions. Dose studies with monoenergetic proton and carbon ions in 12 tissues which showed the largest differences of single energy CT (SECT) to DECT are presented with respect to range uncertainties. The standard approach (SECT) and the new DECT approach are compared to reference Bragg peak positions. Results: Mean deviations to ground truth in mass density predictions could be reduced for soft tissue from (0.5±0.6)% (SECT) to (0.2±0.2)% with the DECT method. Maximum SPR deviations could be reduced significantly for soft tissue from 3.1% (SECT) to 0.7% (DECT) and for bone tissue from 0.8% to 0.1%. MeanI-value deviations could be reduced for soft tissue from (1.1±1.4%, SECT) to (0.4±0.3%) with the presented method. Predictions of elemental composition were improved for every element. Mean and maximum deviations from ground truth of all elemental mass fractions could be reduced by at least a half with DECT compared to SECT (except soft tissue hydrogen and nitrogen where the reduction was slightly smaller). The carbon and oxygen mass fraction predictions profit especially from the DECT information. Dose studies showed that most of the 12 selected tissues would
Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy
Hünemohr, Nora; Paganetti, Harald; Greilich, Steffen; Jäkel, Oliver; Seco, Joao
2014-01-01
Purpose: The authors describe a novel method of predicting mass density and elemental mass fractions of tissues from dual energy CT (DECT) data for Monte Carlo (MC) based dose planning. Methods: The relative electron density ϱe and effective atomic number Zeff are calculated for 71 tabulated tissue compositions. For MC simulations, the mass density is derived via one linear fit in the ϱe that covers the entire range of tissue compositions (except lung tissue). Elemental mass fractions are predicted from the ϱe and the Zeff in combination. Since particle therapy dose planning and verification is especially sensitive to accurate material assignment, differences to the ground truth are further analyzed for mass density, I-value predictions, and stopping power ratios (SPR) for ions. Dose studies with monoenergetic proton and carbon ions in 12 tissues which showed the largest differences of single energy CT (SECT) to DECT are presented with respect to range uncertainties. The standard approach (SECT) and the new DECT approach are compared to reference Bragg peak positions. Results: Mean deviations to ground truth in mass density predictions could be reduced for soft tissue from (0.5±0.6)% (SECT) to (0.2±0.2)% with the DECT method. Maximum SPR deviations could be reduced significantly for soft tissue from 3.1% (SECT) to 0.7% (DECT) and for bone tissue from 0.8% to 0.1%. Mean I-value deviations could be reduced for soft tissue from (1.1±1.4%, SECT) to (0.4±0.3%) with the presented method. Predictions of elemental composition were improved for every element. Mean and maximum deviations from ground truth of all elemental mass fractions could be reduced by at least a half with DECT compared to SECT (except soft tissue hydrogen and nitrogen where the reduction was slightly smaller). The carbon and oxygen mass fraction predictions profit especially from the DECT information. Dose studies showed that most of the 12 selected tissues would profit significantly (up to 2
NMR analysis, protonation equilibria and decomposition kinetics of tolperisone.
Orgován, Gábor; Tihanyi, Károly; Noszál, Béla
2009-12-05
The rate constants of spontaneous and hydroxide-catalyzed decomposition and the tautomer-specific protonation constants of tolperisone, a classical muscle relaxant were determined. A solution NMR method without any separation techniques was elaborated to quantitate the progress of decomposition. All the rate and equilibrium constants were determined at four different temperatures and the activation parameters were calculated. The molecular mechanism of decomposition is proposed.
NASA Astrophysics Data System (ADS)
Erol, Serdar; Serkan Isık, Mustafa; Erol, Bihter
2016-04-01
The recent Earth gravity field satellite missions data lead significant improvement in Global Geopotential Models in terms of both accuracy and resolution. However the improvement in accuracy is not the same everywhere in the Earth and therefore quantifying the level of improvement locally is necessary using the independent data. The validations of the level-3 products from the gravity field satellite missions, independently from the estimation procedures of these products, are possible using various arbitrary data sets, as such the terrestrial gravity observations, astrogeodetic vertical deflections, GPS/leveling data, the stationary sea surface topography. Quantifying the quality of the gravity field functionals via recent products has significant importance for determination of the regional geoid modeling, base on the satellite and terrestrial data fusion with an optimal algorithm, beside the statistical reporting the improvement rates depending on spatial location. In the validations, the errors and the systematic differences between the data and varying spectral content of the compared signals should be considered in order to have comparable results. In this manner this study compares the performance of Wavelet decomposition and spectral enhancement techniques in validation of the GOCE/GRACE based Earth gravity field models using GPS/leveling and terrestrial gravity data in Turkey. The terrestrial validation data are filtered using Wavelet decomposition technique and the numerical results from varying levels of decomposition are compared with the results which are derived using the spectral enhancement approach with contribution of an ultra-high resolution Earth gravity field model. The tests include the GO-DIR-R5, GO-TIM-R5, GOCO05S, EIGEN-6C4 and EGM2008 global models. The conclusion discuss the superiority and drawbacks of both concepts as well as reporting the performance of tested gravity field models with an estimate of their contribution to modeling the
Asadi, Mozaffar; Asadi, Zahra; Savaripoor, Nooshin; Dusek, Michal; Eigner, Vaclav; Shorkaei, Mohammad Ranjkesh; Sedaghat, Moslem
2015-02-05
A series of new VO(IV) complexes of tetradentate N2O2 Schiff base ligands (L(1)-L(4)), were synthesized and characterized by FT-IR, UV-vis and elemental analysis. The structure of the complex VOL(1)⋅DMF was also investigated by X-ray crystallography which revealed a vanadyl center with distorted octahedral coordination where the 2-aza and 2-oxo coordinating sites of the ligand were perpendicular to the "-yl" oxygen. The electrochemical properties of the vanadyl complexes were investigated by cyclic voltammetry. A good correlation was observed between the oxidation potentials and the electron withdrawing character of the substituents on the Schiff base ligands, showing the following trend: MeO
NASA Astrophysics Data System (ADS)
Asadi, Mozaffar; Asadi, Zahra; Savaripoor, Nooshin; Dusek, Michal; Eigner, Vaclav; Shorkaei, Mohammad Ranjkesh; Sedaghat, Moslem
2015-02-01
A series of new VO(IV) complexes of tetradentate N2O2 Schiff base ligands (L1-L4), were synthesized and characterized by FT-IR, UV-vis and elemental analysis. The structure of the complex VOL1ṡDMF was also investigated by X-ray crystallography which revealed a vanadyl center with distorted octahedral coordination where the 2-aza and 2-oxo coordinating sites of the ligand were perpendicular to the "-yl" oxygen. The electrochemical properties of the vanadyl complexes were investigated by cyclic voltammetry. A good correlation was observed between the oxidation potentials and the electron withdrawing character of the substituents on the Schiff base ligands, showing the following trend: MeO < H < Br < Cl. We also studied the thermodynamics of formation of the complexes and kinetic aspects of their thermal decomposition. The formation constants with various substituents on the aldehyde ring follow the trend 5-OMe > 5-H > 5-Br > 5-Cl. Furthermore, the kinetic parameters of thermal decomposition were calculated by using the Coats-Redfern equation. According to the Coats-Redfern plots the kinetics of thermal decomposition of studied complexes is of the first-order in all stages, the free energy of activation for each following stage is larger than the previous one and the complexes have good thermal stability. The preparation of VOL1ṡDMF yielded also another compound, one kind of vanadium oxide [VO]X, with different habitus of crystals, (platelet instead of prisma) and without L1 ligand, consisting of a V10O28 cage, diaminium moiety and dimethylamonium as a counter ions. Because its crystal structure was also new, we reported it along with the targeted complex.
Wang, Dong-Qin; Gao, Ying-Lian; Liu, Jin-Xing; Zheng, Chun-Hou; Kong, Xiang-Zhen
2017-07-18
The traditional methods of drug discovery follow the "one drug-one target" approach, which ignores the cellular and physiological environment of the action mechanism of drugs. However, pathway-based drug discovery methods can overcome this limitation. This kind of method, such as the Integrative Penalized Matrix Decomposition (iPaD) method, identifies the drug-pathway associations by taking the lasso-type penalty on the regularization term. Moreover, instead of imposing the L1-norm regularization, the L2,1-Integrative Penalized Matrix Decomposition (L2,1-iPaD) method imposes the L2,1-norm penalty on the regularization term. In this paper, based on the iPaD and L2,1-iPaD methods, we propose a novel method named L1L2,1-iPaD (L1L2,1-Integrative Penalized Matrix Decomposition), which takes the sum of the L1-norm and L2,1-norm penalties on the regularization term. Besides, we perform permutation test to assess the significance of the identified drug-pathway association pairs and compute the P-values. Compared with the existing methods, our method can identify more drug-pathway association pairs which have been validated in the CancerResource database. In order to identify drug-pathway associations which are not validated in the CancerResource database, we retrieve published papers to prove these associations. The results on two real datasets prove that our method can achieve better enrichment for identified association pairs than the iPaD and L2,1-iPaD methods.
Wang, Dong-Qin; Gao, Ying-Lian; Liu, Jin-Xing; Zheng, Chun-Hou; Kong, Xiang-Zhen
2017-01-01
The traditional methods of drug discovery follow the “one drug-one target” approach, which ignores the cellular and physiological environment of the action mechanism of drugs. However, pathway-based drug discovery methods can overcome this limitation. This kind of method, such as the Integrative Penalized Matrix Decomposition (iPaD) method, identifies the drug-pathway associations by taking the lasso-type penalty on the regularization term. Moreover, instead of imposing the L1-norm regularization, the L2,1-Integrative Penalized Matrix Decomposition (L2,1-iPaD) method imposes the L2,1-norm penalty on the regularization term. In this paper, based on the iPaD and L2,1-iPaD methods, we propose a novel method named L1L2,1-iPaD (L1L2,1-Integrative Penalized Matrix Decomposition), which takes the sum of the L1-norm and L2,1-norm penalties on the regularization term. Besides, we perform permutation test to assess the significance of the identified drug-pathway association pairs and compute the P-values. Compared with the existing methods, our method can identify more drug-pathway association pairs which have been validated in the CancerResource database. In order to identify drug-pathway associations which are not validated in the CancerResource database, we retrieve published papers to prove these associations. The results on two real datasets prove that our method can achieve better enrichment for identified association pairs than the iPaD and L2,1-iPaD methods. PMID:28624800
Adsorption and decomposition of nitrous oxide on zirconia nanoparticles
Miller, T.M.; Grassian, V.H.
1995-12-31
Nitrous oxide, a by-product of several industrial processes, has some environmentally damaging effects. Since it has an atmospheric lifetime of over one hundred years, there is a great deal of interest in finding ways to limit the amount of nitrous oxide emitted into the atmosphere. Recently, zirconia and zirconia-based catalysts have been shown to be effective in catalyzing nitrous oxide decomposition. We have employed FT-IR spectroscopy to study the adsorption and decomposition of nitrous oxide on zirconia nanoparticles. The room temperature IR spectrum of adsorbed nitrous oxide is characterized by two intense absorption bands, the symmetric stretch and asymmetric stretch, that are shifted from the gas phase values. Experiments as a function of sample pretreatment temperature and site-blocker adsorption indicated that nitrous oxide adsorbs on Zr{sup 4+} sites and the mode of attachment is through the oxygen atom. Dissociation of nitrous oxide begins at temperatures above 350{degrees}C. The data suggest that Zr{sup 4+} may be the active site for nitrous oxide decomposition and the room temperature adsorbed species is perhaps a precursor to nitrous oxide decomposition.
Path planning of decentralized multi-quadrotor based on fuzzy-cell decomposition algorithm
NASA Astrophysics Data System (ADS)
Iswanto, Wahyunggoro, Oyas; Cahyadi, Adha Imam
2017-04-01
The paper aims to present a design algorithm for multi quadrotor lanes in order to move towards the goal quickly and avoid obstacles in an area with obstacles. There are several problems in path planning including how to get to the goal position quickly and avoid static and dynamic obstacles. To overcome the problem, therefore, the paper presents fuzzy logic algorithm and fuzzy cell decomposition algorithm. Fuzzy logic algorithm is one of the artificial intelligence algorithms which can be applied to robot path planning that is able to detect static and dynamic obstacles. Cell decomposition algorithm is an algorithm of graph theory used to make a robot path map. By using the two algorithms the robot is able to get to the goal position and avoid obstacles but it takes a considerable time because they are able to find the shortest path. Therefore, this paper describes a modification of the algorithms by adding a potential field algorithm used to provide weight values on the map applied for each quadrotor by using decentralized controlled, so that the quadrotor is able to move to the goal position quickly by finding the shortest path. The simulations conducted have shown that multi-quadrotor can avoid various obstacles and find the shortest path by using the proposed algorithms.
Research on rice acreage estimation in fragmented area based on decomposition of mixed pixels
NASA Astrophysics Data System (ADS)
Zhang, H.; Li, Q. Z.; Lei, F.; Du, X.; Wei, J. D.
2015-04-01
Rice acreage estimation is a key aspect to guarantee food security and also important to support government agricultural subsidy system. In this paper, we explored a sophisticated method to improve rice estimation accuracy at county scale and we developed our approach with China Environment Satellite HJ-1A/B data in Hunan Province, a fragmented area with complex rice cropping patterns. Our approach improved the estimation accuracy by combing supervised and unsupervised classification upon decomposition of mixed pixels model, and the rice estimation results, validated by ground survey data, showed a close relationship (RMSE~3.40) with survey figures, the estimated accuracy (EA) reached 83.74% at county level according to the sub-pixel method, and the accuracy can be increased about 12% compared to the pure-pixel method. The results suggest that decomposition of mixed pixels method has great significance to the improvement of rice acreage estimation accuracy, and can be used in mountainous and broken planting area.
NASA Astrophysics Data System (ADS)
Tachibana, Rie; Näppi, Janne J.; Kim, Se Hyung; Yoshida, Hiroyuki
2015-03-01
CT colonography (CTC) uses orally administered fecal-tagging agents to enhance retained fluid and feces that would otherwise obscure or imitate polyps on CTC images. To visualize the complete region of colon without residual materials, electronic cleansing (EC) can be used to perform virtual subtraction of the tagged materials from CTC images. However, current EC methods produce subtraction artifacts and they can fail to subtract unclearly tagged feces. We developed a novel multi-material EC (MUMA-EC) method that uses dual-energy CTC (DE-CTC) and machine-learning methods to improve the performance of EC. In our method, material decomposition is performed to calculate wateriodine decomposition images and virtual monochromatic (VIM) images. Using the images, a random forest classifier is used to label the regions of lumen air, soft tissue, fecal tagging, and their partial-volume boundaries. The electronically cleansed images are synthesized from the multi-material and VIM image volumes. For pilot evaluation, we acquired the clinical DE-CTC data of 7 patients. Preliminary results suggest that the proposed MUMA-EC method is effective and that it minimizes the three types of image artifacts that were present in previous EC methods.
Functionalization of Tactile Sensation for Robot Based on Haptograph and Modal Decomposition
NASA Astrophysics Data System (ADS)
Yokokura, Yuki; Katsura, Seiichiro; Ohishi, Kiyoshi
In the real world, robots should be able to recognize the environment in order to be of help to humans. A video camera and a laser range finder are devices that can help robots recognize the environment. However, these devices cannot obtain tactile information from environments. Future human-assisting-robots should have the ability to recognize haptic signals, and a disturbance observer can possibly be used to provide the robot with this ability. In this study, a disturbance observer is employed in a mobile robot to functionalize the tactile sensation. This paper proposes a method that involves the use of haptograph and modal decomposition for the haptic recognition of road environments. The haptograph presents a graphic view of the tactile information. It is possible to classify road conditions intuitively. The robot controller is designed by considering the decoupled modal coordinate system, which consists of translational and rotational modes. Modal decomposition is performed by using a quarry matrix. Once the robot is provided with the ability to recognize tactile sensations, its usefulness to humans will increase.
Iterative variational mode decomposition based automated detection of glaucoma using fundus images.
Maheshwari, Shishir; Pachori, Ram Bilas; Kanhangad, Vivek; Bhandary, Sulatha V; Acharya, U Rajendra
2017-09-01
Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition. Various features namely, Kapoor entropy, Renyi entropy, Yager entropy, and fractal dimensions are extracted from VMD components. ReliefF algorithm is used to select the discriminatory features and these features are then fed to the least squares support vector machine (LS-SVM) for classification. Our proposed method achieved classification accuracies of 95.19% and 94.79% using three-fold and ten-fold cross-validation strategies, respectively. This system can aid the ophthalmologists in confirming their manual reading of classes (glaucoma or normal) using fundus images. Copyright © 2017 Elsevier Ltd. All rights reserved.
2010-01-01
Background The inverse problem of fluorescent molecular tomography (FMT) often involves complex large-scale matrix operations, which may lead to unacceptable computational errors and complexity. In this research, a tree structured Schur complement decomposition strategy is proposed to accelerate the reconstruction process and reduce the computational complexity. Additionally, an adaptive regularization scheme is developed to improve the ill-posedness of the inverse problem. Methods The global system is decomposed level by level with the Schur complement system along two paths in the tree structure. The resultant subsystems are solved in combination with the biconjugate gradient method. The mesh for the inverse problem is generated incorporating the prior information. During the reconstruction, the regularization parameters are adaptive not only to the spatial variations but also to the variations of the objective function to tackle the ill-posed nature of the inverse problem. Results Simulation results demonstrate that the strategy of the tree structured Schur complement decomposition obviously outperforms the previous methods, such as the conventional Conjugate-Gradient (CG) and the Schur CG methods, in both reconstruction accuracy and speed. As compared with the Tikhonov regularization method, the adaptive regularization scheme can significantly improve ill-posedness of the inverse problem. Conclusions The methods proposed in this paper can significantly improve the reconstructed image quality of FMT and accelerate the reconstruction process. PMID:20482886
NASA Astrophysics Data System (ADS)
Lezina, Natalya; Agoshkov, Valery
2017-04-01
Domain decomposition method (DDM) allows one to present a domain with complex geometry as a set of essentially simpler subdomains. This method is particularly applied for the hydrodynamics of oceans and seas. In each subdomain the system of thermo-hydrodynamic equations in the Boussinesq and hydrostatic approximations is solved. The problem of obtaining solution in the whole domain is that it is necessary to combine solutions in subdomains. For this purposes iterative algorithm is created and numerical experiments are conducted to investigate an effectiveness of developed algorithm using DDM. For symmetric operators in DDM, Poincare-Steklov's operators [1] are used, but for the problems of the hydrodynamics, it is not suitable. In this case for the problem, adjoint equation method [2] and inverse problem theory are used. In addition, it is possible to create algorithms for the parallel calculations using DDM on multiprocessor computer system. DDM for the model of the Baltic Sea dynamics is numerically studied. The results of numerical experiments using DDM are compared with the solution of the system of hydrodynamic equations in the whole domain. The work was supported by the Russian Science Foundation (project 14-11-00609, the formulation of the iterative process and numerical experiments). [1] V.I. Agoshkov, Domain Decompositions Methods in the Mathematical Physics Problem // Numerical processes and systems, No 8, Moscow, 1991 (in Russian). [2] V.I. Agoshkov, Optimal Control Approaches and Adjoint Equations in the Mathematical Physics Problem, Institute of Numerical Mathematics, RAS, Moscow, 2003 (in Russian).
Lee, Byung Il; Lee, Suk-Ho; Kim, Tae-Seong; Kwon, Ohin; Woo, Eung Je; Seo, Jin Keun
2005-11-01
Recent progress in magnetic resonance electrical impedance tomography (MREIT) research via simulation and biological tissue phantom studies have shown that conductivity images with higher spatial resolution and accuracy are achievable. In order to apply MREIT to human subjects, one of the important remaining problems to be solved is to reduce the amount of the injection current such that it meets the electrical safety regulations. However, by limiting the amount of the injection current according to the safety regulations, the measured MR data such as the z-component of magnetic flux density Bz in MREIT tend to have low SNR and get usually degraded in their accuracy due to the nonideal data acquisition system of an MR scanner. Furthermore, numerical differentiations of the measured Bz required by the conductivity image reconstruction algorithms tend to further deteriorate the quality and accuracy of the reconstructed conductivity images. In this paper, we propose a denoising technique that incorporates a harmonic decomposition. The harmonic decomposition is especially suitable for MREIT due to the physical characteristics of Bz. It effectively removes systematic and random noises, while preserving important key features in the MR measurements, so that improved conductivity images can be obtained. The simulation and experimental results demonstrate that the proposed denoising technique is effective for MREIT, producing significantly improved quality of conductivity images. The denoising technique will be a valuable tool in MREIT to reduce the amount of the injection current when it is combined with an improved MREIT pulse sequence.
Automated polyp measurement based on colon structure decomposition for CT colonography
NASA Astrophysics Data System (ADS)
Wang, Huafeng; Li, Lihong C.; Han, Hao; Peng, Hao; Song, Bowen; Wei, Xinzhou; Liang, Zhengrong
2014-03-01
Accurate assessment of colorectal polyp size is of great significance for early diagnosis and management of colorectal cancers. Due to the complexity of colon structure, polyps with diverse geometric characteristics grow from different landform surfaces. In this paper, we present a new colon decomposition approach for polyp measurement. We first apply an efficient maximum a posteriori expectation-maximization (MAP-EM) partial volume segmentation algorithm to achieve an effective electronic cleansing on colon. The global colon structure is then decomposed into different kinds of morphological shapes, e.g. haustral folds or haustral wall. Meanwhile, the polyp location is identified by an automatic computer aided detection algorithm. By integrating the colon structure decomposition with the computer aided detection system, a patch volume of colon polyps is extracted. Thus, polyp size assessment can be achieved by finding abnormal protrusion on a relative uniform morphological surface from the decomposed colon landform. We evaluated our method via physical phantom and clinical datasets. Experiment results demonstrate the feasibility of our method in consistently quantifying the size of polyp volume and, therefore, facilitating characterizing for clinical management.
Adaptive multi-step Full Waveform Inversion based on Waveform Mode Decomposition
NASA Astrophysics Data System (ADS)
Hu, Yong; Han, Liguo; Xu, Zhuo; Zhang, Fengjiao; Zeng, Jingwen
2017-04-01
Full Waveform Inversion (FWI) can be used to build high resolution velocity models, but there are still many challenges in seismic field data processing. The most difficult problem is about how to recover long-wavelength components of subsurface velocity models when seismic data is lacking of low frequency information and without long-offsets. To solve this problem, we propose to use Waveform Mode Decomposition (WMD) method to reconstruct low frequency information for FWI to obtain a smooth model, so that the initial model dependence of FWI can be reduced. In this paper, we use adjoint-state method to calculate the gradient for Waveform Mode Decomposition Full Waveform Inversion (WMDFWI). Through the illustrative numerical examples, we proved that the low frequency which is reconstructed by WMD method is very reliable. WMDFWI in combination with the adaptive multi-step inversion strategy can obtain more faithful and accurate final inversion results. Numerical examples show that even if the initial velocity model is far from the true model and lacking of low frequency information, we still can obtain good inversion results with WMD method. From numerical examples of anti-noise test, we see that the adaptive multi-step inversion strategy for WMDFWI has strong ability to resist Gaussian noise. WMD method is promising to be able to implement for the land seismic FWI, because it can reconstruct the low frequency information, lower the dominant frequency in the adjoint source, and has a strong ability to resist noise.
Wimmer, Eric; Borghèse, Sophie; Blanc, Aurélien; Bénéteau, Valérie; Pale, Patrick
2017-01-31
Similarly to polymer-supported assisted synthesis (PSAS), organic synthesis could be envisaged being performed by using zeolites, native or metal-doped, as heterogeneous catalysts. To illustrate this unprecedented Zeolite-Based Organic Synthesis (ZeoBOS), the total synthesis of acortatarin A was achieved through a novel strategy and using five out of eleven synthetic steps catalyzed by H- or metal-doped zeolites as catalysts. Notably, the formation of an yne-pyrrole intermediate with a copper-doped zeolite and the spiroketalization of an alkyne diol with a silver-doped zeolite have been developed as key steps of the synthesis.
Sharma, Akhilesh K; Sunoj, Raghavan B
2012-12-07
The stereocontrolling transition state (TS) models for C-C bond formation relying on hydrogen bonding have generally been successful in proline-catalyzed aldol, Mannich, α-amination, and α-aminoxylation reactions. However, the suitability of the hydrogen-bonding model in protic and aprotic conditions as well as under basic and base-free conditions has not been well established for Michael reactions. Through a comprehensive density functional theory investigation, we herein analyze different TS models for the stereocontrolling C-C bond formation, both in the presence and absence of a base in an aprotic solvent (THF). A refined stereocontrolling TS for the Michael reaction between cyclohexanone and nitrostyrene is proposed. The new TS devoid of hydrogen bonding between the nitro group of nitrostyrene and carboxylic acid of proline, under base-free conditions, is found to be more preferred over the conventional hydrogen-bonding model besides being able to reproduce the experimentally observed stereochemical outcome. A DBU-bound TS is identified as more suitable for rationalizing the origin of asymmetric induction under basic reaction conditions. In both cases, the most preferred approach of nitrostyrene is identified as occurring from the face anti to the carboxylic acid of proline-enamine. The predicted enantio- and diastereoselectivities are in very good agreement with the experimental observations.
NASA Astrophysics Data System (ADS)
Sosnin, E. A.; Matafonova, G. G.; Batoev, V. B.; Christofi, N.
2008-01-01
The combined decomposition method of chlorophenols (CP) is offered. The method is based on photolysis of CP through XeBr-excilamp UV irradiation at 283 nm in a flow photoreactor with subsequent treatment of photolysis products by microorganism-destructor B. cereus isolated from an aeration pond of Baikal pulp-and-paper mill. At initial concentration of CP of 20 mg/l the polluted solutions can be utilized directly by means of biological treatment using B. cereus under aerobic conditions. However, if the initial CP concentration is higher than 20 mg/l, the polluted solutions are low biodegradable. It is shown, that the combined treatment is most effective method in this case. At initial CP concentration of 50 mg/l and higher it is suggested to use the deep preliminary UV-treatment with the purpose of removal 80-90 % of initial CP. It is revealed, that 4-CP is relatively persistent compound for B. cereus, easily decomposed by UV-radiation of XeBr-excilamp. As a result of subsequent biological treatment during 10 days the utilization of basic CP photoproducts is obtained. Experimentally, the preliminary UV-processing time was essentially less than that found earlier by E. Tamer, Z. Hamid, Aly A. (Chemosphere, 2006), where the half-life periods of initial CP were from 2.2 to 54 hours at the same value of initial concentration of CP. Correspondingly, the total CP decomposition process was accompanied by high power inputs. It is suggested to use mentioned above method for effective CP decomposition at high concentration values.
NASA Astrophysics Data System (ADS)
Li, Xibing; Shang, Xueyi; Morales-Esteban, A.; Wang, Zewei
2017-03-01
Seismic P phase arrival picking of weak events is a difficult problem in seismology. The algorithm proposed in this research is based on Empirical Mode Decomposition (EMD) and on the Akaike Information Criterion (AIC) picker. It has been called the EMD-AIC picker. The EMD is a self-adaptive signal decomposition method that not only improves Signal to Noise Ratio (SNR) but also retains P phase arrival information. Then, P phase arrival picking has been determined by applying the AIC picker to the selected main Intrinsic Mode Functions (IMFs). The performance of the EMD-AIC picker has been evaluated on the basis of 1938 micro-seismic signals from the Yongshaba mine (China). The P phases identified by this algorithm have been compared with manual pickings. The evaluation results confirm that the EMD-AIC pickings are highly accurate for the majority of the micro-seismograms. Moreover, the pickings are independent of the kind of noise. Finally, the results obtained by this algorithm have been compared to the wavelet based Discrete Wavelet Transform (DWT)-AIC pickings. This comparison has demonstrated that the EMD-AIC picking method has a better picking accuracy than the DWT-AIC picking method, thus showing this method's reliability and potential.
NASA Astrophysics Data System (ADS)
Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi
2014-01-01
The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.
Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi
2014-01-01
A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals' separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system.
Shen, Xuehua; Xiong, Qingyu; Shi, Xin; Wang, Kai; Liang, Shan; Gao, Min
2015-09-01
Temperature distribution reconstruction is of critical importance for circular area, and an ultrasonic technique is investigated to meet this demand in this paper. Considering the particularity of circular area, algorithm based on Markov radial basis approximation and singular value decomposition is proposed, while ultrasonic transducers layout and division of measured area are properly designed. The reconstruction performance is validated via numerical experiments using different temperature distribution models, and is compared with algorithm based on least square method. To study the anti-interference, various noises are adding to the theoretical value of time-of-flight. Experiment results indicate that the proposed algorithm can reconstruct temperature distribution with higher accuracy and stronger anti-interference, while without the problem of algorithm based on least square method that its reconstructions will lose much temperature information near the edge of measured area. Copyright © 2015 Elsevier B.V. All rights reserved.
Bearing fault detection based on hybrid ensemble detector and empirical mode decomposition
NASA Astrophysics Data System (ADS)
Georgoulas, George; Loutas, Theodore; Stylios, Chrysostomos D.; Kostopoulos, Vassilis
2013-12-01
Aiming at more efficient fault diagnosis, this research work presents an integrated anomaly detection approach for seeded bearing faults. Vibration signals from normal bearings and bearings with three different fault locations, as well as different fault sizes and loading conditions are examined. The Empirical Mode Decomposition and the Hilbert Huang transform are employed for the extraction of a compact feature set. Then, a hybrid ensemble detector is trained using data coming only from the normal bearings and it is successfully applied for the detection of any deviation from the normal condition. The results prove the potential use of the proposed scheme as a first stage of an alarm signalling system for the detection of bearing faults irrespective of their loading condition.
Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
NASA Astrophysics Data System (ADS)
Cabrera, Diego; Sancho, Fernando; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Li, Chuan; Vásquez, Rafael E.
2015-09-01
This paper addresses the development of a random forest classifier for the multi-class fault diagnosis in spur gearboxes. The vibration signal's condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients' energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters' space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.
A non-orthogonal SVD-based decomposition for phase invariant error-related potential estimation.
Phlypo, Ronald; Jrad, Nisrine; Rousseau, Sandra; Congedo, Marco
2011-01-01
The estimation of the Error Related Potential from a set of trials is a challenging problem. Indeed, the Error Related Potential is of low amplitude compared to the ongoing electroencephalographic activity. In addition, simple summing over the different trials is prone to errors, since the waveform does not appear at an exact latency with respect to the trigger. In this work, we propose a method to cope with the discrepancy of these latencies of the Error Related Potential waveform and offer a framework in which the estimation of the Error Related Potential waveform reduces to a simple Singular Value Decomposition of an analytic waveform representation of the observed signal. The followed approach is promising, since we are able to explain a higher portion of the variance of the observed signal with fewer components in the expansion.
NASA Astrophysics Data System (ADS)
Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi
2017-03-01
The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert–Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.
Multiresolution motion planning for autonomous agents via wavelet-based cell decompositions.
Cowlagi, Raghvendra V; Tsiotras, Panagiotis
2012-10-01
We present a path- and motion-planning scheme that is "multiresolution" both in the sense of representing the environment with high accuracy only locally and in the sense of addressing the vehicle kinematic and dynamic constraints only locally. The proposed scheme uses rectangular multiresolution cell decompositions, efficiently generated using the wavelet transform. The wavelet transform is widely used in signal and image processing, with emerging applications in autonomous sensing and perception systems. The proposed motion planner enables the simultaneous use of the wavelet transform in both the perception and in the motion-planning layers of vehicle autonomy, thus potentially reducing online computations. We rigorously prove the completeness of the proposed path-planning scheme, and we provide numerical simulation results to illustrate its efficacy.
NASA Astrophysics Data System (ADS)
Zhao, Tao; Hwang, Feng-Nan; Cai, Xiao-Chuan
2016-07-01
We consider a quintic polynomial eigenvalue problem arising from the finite volume discretization of a quantum dot simulation problem. The problem is solved by the Jacobi-Davidson (JD) algorithm. Our focus is on how to achieve the quadratic convergence of JD in a way that is not only efficient but also scalable when the number of processor cores is large. For this purpose, we develop a projected two-level Schwarz preconditioned JD algorithm that exploits multilevel domain decomposition techniques. The pyramidal quantum dot calculation is carefully studied to illustrate the efficiency of the proposed method. Numerical experiments confirm that the proposed method has a good scalability for problems with hundreds of millions of unknowns on a parallel computer with more than 10,000 processor cores.
An improved infrared image enhancement algorithm based on multi-scale decomposition
NASA Astrophysics Data System (ADS)
Zhang, Honghui; Luo, Haibo; Yu, Xin-rong; Ding, Qing-hai
2014-11-01
Due to the restriction of infrared imaging component and the radiation of atmosphere, infrared images are discontented with image contrast, blurry, large yawp. Aimed on these problems, a multi-scale image enhancement algorithm is proposed. The main principle is as follows: firstly, On the basis of the multi-scale image decomposition, We use an edge-preserving spatial filter that instead of the Gaussion filter proposed in the original version, adjust the scale-dependent factor With a weighted information. Secondly, contrast is equalized by applying nonlinear amplification. Thirdly, subband image is the weighted sum of sampled subband image and subsampled then upsampled subband image by a factor of two. Finally, Image reconstruction was applied. Experiment results show that the proposed method can enhance the original infrared image effectively and improve the contrast, moreover, it also can reserve the details and edges of the image well.
NASA Astrophysics Data System (ADS)
Xian, Lu; He, Kaijian; Lai, Kin Keung
2016-07-01
In recent years, the increasing level of volatility of the gold price has received the increasing level of attention from the academia and industry alike. Due to the complexity and significant fluctuations observed in the gold market, however, most of current approaches have failed to produce robust and consistent modeling and forecasting results. Ensemble Empirical Model Decomposition (EEMD) and Independent Component Analysis (ICA) are novel data analysis methods that can deal with nonlinear and non-stationary time series. This study introduces a new methodology which combines the two methods and applies it to gold price analysis. This includes three steps: firstly, the original gold price series is decomposed into several Intrinsic Mode Functions (IMFs) by EEMD. Secondly, IMFs are further processed with unimportant ones re-grouped. Then a new set of data called Virtual Intrinsic Mode Functions (VIMFs) is reconstructed. Finally, ICA is used to decompose VIMFs into statistically Independent Components (ICs). The decomposition results reveal that the gold price series can be represented by the linear combination of ICs. Furthermore, the economic meanings of ICs are analyzed and discussed in detail, according to the change trend and ICs' transformation coefficients. The analyses not only explain the inner driving factors and their impacts but also conduct in-depth analysis on how these factors affect gold price. At the same time, regression analysis has been conducted to verify our analysis. Results from the empirical studies in the gold markets show that the EEMD-ICA serve as an effective technique for gold price analysis from a new perspective.
Sharma, Govind K; Kumar, Anish; Jayakumar, T; Purnachandra Rao, B; Mariyappa, N
2015-03-01
A signal processing methodology is proposed in this paper for effective reconstruction of ultrasonic signals in coarse grained high scattering austenitic stainless steel. The proposed methodology is comprised of the Ensemble Empirical Mode Decomposition (EEMD) processing of ultrasonic signals and application of signal minimisation algorithm on selected Intrinsic Mode Functions (IMFs) obtained by EEMD. The methodology is applied to ultrasonic signals obtained from austenitic stainless steel specimens of different grain size, with and without defects. The influence of probe frequency and data length of a signal on EEMD decomposition is also investigated. For a particular sampling rate and probe frequency, the same range of IMFs can be used to reconstruct the ultrasonic signal, irrespective of the grain size in the range of 30-210 μm investigated in this study. This methodology is successfully employed for detection of defects in a 50mm thick coarse grain austenitic stainless steel specimens. Signal to noise ratio improvement of better than 15 dB is observed for the ultrasonic signal obtained from a 25 mm deep flat bottom hole in 200 μm grain size specimen. For ultrasonic signals obtained from defects at different depths, a minimum of 7 dB extra enhancement in SNR is achieved as compared to the sum of selected IMF approach. The application of minimisation algorithm with EEMD processed signal in the proposed methodology proves to be effective for adaptive signal reconstruction with improved signal to noise ratio. This methodology was further employed for successful imaging of defects in a B-scan.
Surface EMG Decomposition Based on K-means Clustering and Convolution Kernel Compensation
Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun
2015-01-01
A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multi-channel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multi-step iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering - Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of −10dB. Over 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A ‘two-source’ test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multi-channel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction. PMID:25486655
Surface EMG decomposition based on K-means clustering and convolution kernel compensation.
Ning, Yong; Zhu, Xiangjun; Zhu, Shanan; Zhang, Yingchun
2015-03-01
A new approach has been developed by combining the K-mean clustering (KMC) method and a modified convolution kernel compensation (CKC) method for multichannel surface electromyogram (EMG) decomposition. The KMC method was first utilized to cluster vectors of observations at different time instants and then estimate the initial innervation pulse train (IPT). The CKC method, modified with a novel multistep iterative process, was conducted to update the estimated IPT. The performance of the proposed K-means clustering-Modified CKC (KmCKC) approach was evaluated by reconstructing IPTs from both simulated and experimental surface EMG signals. The KmCKC approach successfully reconstructed all 10 IPTs from the simulated surface EMG signals with true positive rates (TPR) of over 90% with a low signal-to-noise ratio (SNR) of -10 dB. More than 10 motor units were also successfully extracted from the 64-channel experimental surface EMG signals of the first dorsal interosseous (FDI) muscles when a contraction force was held at 8 N by using the KmCKC approach. A "two-source" test was further conducted with 64-channel surface EMG signals. The high percentage of common MUs and common pulses (over 92% at all force levels) between the IPTs reconstructed from the two independent groups of surface EMG signals demonstrates the reliability and capability of the proposed KmCKC approach in multichannel surface EMG decomposition. Results from both simulated and experimental data are consistent and confirm that the proposed KmCKC approach can successfully reconstruct IPTs with high accuracy at different levels of contraction.
Beletskaya, Irina P; Afanasiev, Vladimir V; Kazankova, Marina A; Efimova, Irina V
2003-11-13
[reaction: see text] The first example of direct phosphination of terminal alkynes with chlorophosphanes catalyzed by Ni or Pd complexes is described. Both aromatic and aliphatic terminal acetylenes undergo the coupling reaction to give corresponding coupling product in high yield.
NASA Astrophysics Data System (ADS)
Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu
2016-06-01
To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.
Ultrafast degradation of azo dyes catalyzed by cobalt-based metallic glass
NASA Astrophysics Data System (ADS)
Qin, X. D.; Zhu, Z. W.; Liu, G.; Fu, H. M.; Zhang, H. W.; Wang, A. M.; Li, H.; Zhang, H. F.
2015-12-01
Reactivity and mass loss are considered mutually exclusive in conventional zero-valent metal (ZVM) technology to treat environmental contaminants. Here, we report the outstanding performance of Co-based metallic glass (MG) in degrading an aqueous solution of azo dye, thus eliminating this trade-off. Ball-milled Co-based MG powders completely degrade Acid Orange II at an ultrafast rate. The surface-area-normalized rate constant of Co-based MG powders was one order of magnitude higher than that of Co-based crystalline counterparts and three orders of magnitude higher than that of the widely studied Fe0 powders. The coordinatively unsaturated local structure in Co-based MG responds to the catalysis for degradation, resulting in very low mass loss. Wide applicability and good reusability were also present. Co-based MG is the most efficient material for azo dye degradation reported thus far, and will promote the practical application of MGs as functional materials.
Cai, C; Rodet, T; Legoupil, S; Mohammad-Djafari, A
2013-11-01
Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images. This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed. The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the
Cai, C.; Rodet, T.; Mohammad-Djafari, A.; Legoupil, S.
2013-11-15
Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also
Kako, Tetsuya; Meng, Xianguang; Ye, Jinhua
2015-10-01
Composite of NaBiO{sub 3}-loaded WO{sub 3} with a mixing ratio of 10:100 was prepared for photocatalytic harmful-organic-contaminant decomposition. The composite properties were measured using X-ray diffraction, ultraviolet-visible spectrophotometer (UV-Vis), and valence band-X-ray photoelectron spectroscope (VB-XPS). The results exhibited that the potentials for top of the valence band and bottom of conduction band for NaBiO{sub 3} can be estimated, respectively, as +2.5 V and -0.1 to 0 V. Furthermore, WO{sub 3}, NaBiO{sub 3}, and the composite showed IPA oxidation properties under visible-light irradiation. Results show that the composite exhibited much higher photocatalytic activity about 2-propanol (IPA) decomposition into CO{sub 2} than individual WO{sub 3} or NaBiO{sub 3} because of charge separation promotion and the base effect of NaBiO{sub 3}.
Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E
2016-07-15
Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.
Czirják, Gábor
2015-11-01
Grooves and pockets on the surface, channels through the protein, the chambers or cavities, and the tunnels connecting the internal points to each other or to the external fluid environment are fundamental determinants of a wide range of biological functions. PrinCCes (Protein internal Channel & Cavity estimation) is a computer program supporting the visualization of voids. It includes a novel algorithm for the decomposition of the entire void volume of the protein or protein complex to individual entities. The decomposition is based on continuity. An individual void is defined by uninterrupted extension in space: a spherical probe can freely move between any two internal locations of a continuous void. Continuous voids are detected irrespective of their topological complexity, they may contain any number of holes and bifurcations. The voids of a protein can be visualized one by one or in combinations as triangulated surfaces. The output is automatically exported to free VMD (Visual Molecular Dynamics) or Chimera software, allowing the 3D rotation of the surfaces and the production of publication quality images. PrinCCes with graphic user interface and command line versions are available for MS Windows and Linux. The source code and executable can be downloaded at any of the following links: http://scholar.semmelweis.hu/czirjakgabor/s/princces/#t1 https://github.com/CzirjakGabor/PrinCCes http://1drv.ms/1bP9iJ3. Copyright © 2015 Elsevier Inc. All rights reserved.
Optimal domain decomposition strategies
NASA Technical Reports Server (NTRS)
Yoon, Yonghyun; Soni, Bharat K.
1995-01-01
The primary interest of the authors is in the area of grid generation, in particular, optimal domain decomposition about realistic configurations. A grid generation procedure with optimal blocking strategies has been developed to generate multi-block grids for a circular-to-rectangular transition duct. The focus of this study is the domain decomposition which optimizes solution algorithm/block compatibility based on geometrical complexities as well as the physical characteristics of flow field. The progress realized in this study is summarized in this paper.
Batch Microreactor Studies of Base Catalyzed Ligin Depolymerization in Alcohol Solvents
Evans, L.; Littlewolf, A.; Lopez, M.; Miller, J.E.
1999-02-03
The depolymerization of organosolv-derived lignins by bases in methanol or ethanol solvent was studied in rapidly heated batch microreactors. The conversion of lignin to ether solubles by KOH in methanol or ethanol was rapid at 290 "C, reaching the maximum value within 10-15 minutes. An excess of base relative to Lignin monomer units was required for maximum conversion. Strong bases (KOH, NaOH, CSOH) convert more of the lignin to ether soluble material than do weaker bases LiOH, Ca(OH)2, and NacCO2). Ethanol and methanol are converted to acetic and formic acid respectively under the reaction conditions with an activation energy of approximately 50 kcal/mol. This results in a loss of solvent, but more importantly neutralizes the base catalyst, halting forward progress of the reaction.
Neurock, Matthew; Tao, Zhiyuan; Chemburkar, Ashwin; Hibbitts, David D; Iglesia, Enrique
2017-03-23
Condensation and esterification are important catalytic routes in the conversion of polyols and oxygenates derived from biomass to fuels and chemical intermediates. Previous experimental studies show that alkanal, alkanol and hydrogen mixtures equilibrate over Cu/SiO2 and form surface alkoxides and alkanals that subsequently promote condensation and esterification reactions. First-principle density functional theory (DFT) calculations were carried out herein to elucidate the elementary paths and the corresponding energetics for the interconversion of propanal + H2 to propanol and the subsequent C-C and C-O bond formation paths involved in aldol condensation and esterification of these mixtures over model Cu surfaces. Propanal and hydrogen readily equilibrate with propanol via C-H and O-H addition steps to form surface propoxide intermediates and equilibrated propanal/propanol mixtures. Surface propoxides readily form via low energy paths involving a hydrogen addition to the electrophilic carbon center of the carbonyl of propanal or via a proton transfer from an adsorbed propanol to a vicinal propanal. The resulting propoxide withdraws electron density from the surface and behaves as a base catalyzing the activation of propanal and subsequent esterification and condensation reactions. These basic propoxides can readily abstract the acidic Cα-H of propanal to produce the CH3CH((-))CH2O* enolate, thus initiating aldol condensation. The enolate can subsequently react with a second adsorbed propanal to form a C-C bond and a β-alkoxide alkanal intermediate. The β-alkoxide alkanal can subsequently undergo facile hydride transfer to form the 2-formyl-3-pentanone intermediate that decarbonylates to give the 3-pentanone product. Cu is unique in that it rapidly catalyzes the decarbonylation of the C2n intermediates to form C2n-1 3-pentanone as the major product with very small yields of C2n products. This is likely due to the absence of Brønsted acid sites, present on
Envisioning an enzymatic Diels-Alder reaction by in situ acid-base catalyzed diene generation.
Linder, Mats; Johansson, Adam Johannes; Manta, Bianca; Olsson, Philip; Brinck, Tore
2012-06-07
We present and evaluate a new and potentially efficient route for enzyme-mediated Diels-Alder reactions, utilizing general acid-base catalysis. The viability of employing the active site of ketosteroid isomerase is demonstrated.
A dual Lewis base activation strategy for enantioselective carbene-catalyzed annulations.
Izquierdo, Javier; Orue, Ane; Scheidt, Karl A
2013-07-24
A dual activation strategy integrating N-heterocyclic carbene (NHC) catalysis and a second Lewis base has been developed. NHC-bound homoenolate equivalents derived from α,β-unsaturated aldehydes combine with transient reactive o-quinone methides in an enantioselective formal [4 + 3] fashion to access 2-benzoxopinones. The overall approach provides a general blueprint for the integration of carbene catalysis with additional Lewis base activation modes.
Ultrafast degradation of azo dyes catalyzed by cobalt-based metallic glass
Qin, X. D.; Zhu, Z. W.; Liu, G.; Fu, H. M.; Zhang, H. W.; Wang, A. M.; Li, H.; Zhang, H. F.
2015-01-01
Reactivity and mass loss are considered mutually exclusive in conventional zero-valent metal (ZVM) technology to treat environmental contaminants. Here, we report the outstanding performance of Co-based metallic glass (MG) in degrading an aqueous solution of azo dye, thus eliminating this trade-off. Ball-milled Co-based MG powders completely degrade Acid Orange II at an ultrafast rate. The surface-area-normalized rate constant of Co-based MG powders was one order of magnitude higher than that of Co-based crystalline counterparts and three orders of magnitude higher than that of the widely studied Fe0 powders. The coordinatively unsaturated local structure in Co-based MG responds to the catalysis for degradation, resulting in very low mass loss. Wide applicability and good reusability were also present. Co-based MG is the most efficient material for azo dye degradation reported thus far, and will promote the practical application of MGs as functional materials. PMID:26656918
Yang, Zhe-Han; Zhuo, Ying; Yuan, Ruo; Chai, Ya-Qin
2015-05-20
An alkaline phosphatase (ALP)-based biosensor can in situ generate an electroactive product by enzymatic hydrolysis of inactive substrates. To obtain a higher signal-to-background ratio, a chemical redox cycling signal-amplified strategy based on the addition of a strong reducing agent has often be applied in the construction of ALP-based biosensors. However, the strong reducing agent not only affects the activity of ALP but also readily reacts with dissolved oxygen, leading to inaccurate results. In this work, a new signal-amplified strategy for a thrombin (TB) aptasensor based on the catalytic oxidation of ALP-generated products, 1-naphthol (NP), using hemin/G-quadruplex DNAzymes was reported. We implemented gold-nanoparticle-decorated zinc oxide nanoflowers (Au-ZnO) as the matrix for immobilizing ALP and TB aptamer (TBA) and then labeled it with hemin to form hemin/G-quadruplex/ALP/Au-ZnO bioconjugates (TBA II bioconjugates). Through a "sandwich" reaction, TBA II bioconjugates were captured on the electrode surface. The amplified signal was carried out in two steps: (i) an ALP-catalyzed inactive substrate, 1-naphthyl phosphate (NPP), in situ produces NP on the surface of the electrode; (ii) on the one hand, NP as a new reactant could be directly electrooxidized and generated an electrochemical signal, but, on the other hand, NP could be oxidized by hemin/G-quadruplex in the presence of H2O2, resulting in amplification of the electrochemical signal. The proposed TB aptasensor achieved a linear range of 1 pM to 30 nM with a detection limit of 0.37 pM (defined as S/N = 3).
Verma, Pragya; Patni, Priya A; Sunoj, Raghavan B
2011-07-15
The density functional theory investigation on the mechanism of NHC-catalyzed cycloannulation reaction of the homoenolate derived from butenal with pentenone is studied. The M06-2X/6-31+G** and B3LYP/6-31+G** levels of theory, including the effect of continuum solvation in dichloromethane and tetrahydrofuran, are employed. Several mechanistic scenarios are examined for each elementary step by identifying the key intermediates and the corresponding transition states interconnecting them on the respective potential energy surfaces. Both assisted and unassisted pathways for important proton transfer steps are considered, respectively, with and without the explicit inclusion of base (DBU) in the corresponding transition states. The barrier for the crucial proton transfer steps involved in the formation of the Breslow intermediate as well as in the subsequent steps is found to be significantly lowered by explicit inclusion of DBU. The energetic comparison between two key pathways, depicted as path A and path B, respectively, leading to cyclopentene and cyclopentanone derivatives, is performed. The major mechanistic bifurcation has been identified as emanating from the site of enolization of the initial zwitterionic intermediate resulting from the addition of a homoenolate equivalent to enone. If the enolization occurs nearer to the NHC moiety, the reaction is likely to proceed through path A, leading to cyclopentene. The enolization away from NHC leads to cyclopentanone product through path B. The computed results are generally in good agreement with the reported experimental results.
Shokhen, Michael; Albeck, Amnon
2004-05-01
General acid-base catalysis is a key element of the catalytic activity of most enzymes. Therefore, any explicit molecular modeling of enzyme-catalyzed chemical reactions requires correct identification of protons location on the catalytic groups. In this work, we apply our quantum mechanical/self-consistent reaction field in virtual solvent [QM/SCRF(VS)] method for identification of the position of protons shared by the enzyme catalytic groups and the polar groups of the inhibitor in a covalent tetrahedral complex (TC) of the hepatitis C virus NS3 protease with a peptidyl alpha-ketoacid inhibitor. To identify the relevant protonation states, we have analyzed relative stabilities of R and S configurations of the TC that depend on the specific proton distribution over the polar groups and correlated it with experimental NMR and X-ray crystallography data, both at low and neutral pH ranges. The tentative assignment of the single resonance in the (13)C NMR spectrum of the hemiketal carbon at physiological pH to the S configuration of TC is confirmed. Both R and S configurations are equally stable at acidic pH in our modeling, in good agreement with the (13)C NMR observation. Copyright 2004 Wiley-Liss, Inc.
Bifunctional Brønsted Base Catalyzes Direct Asymmetric Aldol Reaction of α-Keto Amides.
Echave, Haizea; López, Rosa; Palomo, Claudio
2016-03-01
The first enantioselective direct cross-aldol reaction of α-keto amides with aldehydes, mediated by a bifunctional ureidopeptide-based Brønsted base catalyst, is described. The appropriate combination of a tertiary amine base and an aminal, and urea hydrogen-bond donor groups in the catalyst structure promoted the exclusive generation of the α-keto amide enolate which reacted with either non-enolizable or enolizable aldehydes to produce highly enantioenriched polyoxygenated aldol adducts without side-products resulting from dehydration, α-keto amide self-condensation, aldehyde enolization, and isotetronic acid formation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Michaud, Jean-Philippe; Moreau, Gaétan
2011-01-01
Using pig carcasses exposed over 3 years in rural fields during spring, summer, and fall, we studied the relationship between decomposition stages and degree-day accumulation (i) to verify the predictability of the decomposition stages used in forensic entomology to document carcass decomposition and (ii) to build a degree-day accumulation model applicable to various decomposition-related processes. Results indicate that the decomposition stages can be predicted with accuracy from temperature records and that a reliable degree-day index can be developed to study decomposition-related processes. The development of degree-day indices opens new doors for researchers and allows for the application of inferential tools unaffected by climatic variability, as well as for the inclusion of statistics in a science that is primarily descriptive and in need of validation methods in courtroom proceedings.
NASA Astrophysics Data System (ADS)
Qian, Xi-Yuan; Gu, Gao-Feng; Zhou, Wei-Xing
2011-11-01
Detrended fluctuation analysis (DFA) is a simple but very efficient method for investigating the power-law long-term correlations of non-stationary time series, in which a detrending step is necessary to obtain the local fluctuations at different timescales. We propose to determine the local trends through empirical mode decomposition (EMD) and perform the detrending operation by removing the EMD-based local trends, which gives an EMD-based DFA method. Similarly, we also propose a modified multifractal DFA algorithm, called an EMD-based MFDFA. The performance of the EMD-based DFA and MFDFA methods is assessed with extensive numerical experiments based on fractional Brownian motion and multiplicative cascading process. We find that the EMD-based DFA method performs better than the classic DFA method in the determination of the Hurst index when the time series is strongly anticorrelated and the EMD-based MFDFA method outperforms the traditional MFDFA method when the moment order q of the detrended fluctuations is positive. We apply the EMD-based MFDFA to the 1 min data of Shanghai Stock Exchange Composite index, and the presence of multifractality is confirmed. We also analyze the daily Austrian electricity prices and confirm its anti-persistence.
An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation
NASA Technical Reports Server (NTRS)
Litt, Jonathan S.
2007-01-01
A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.
An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation
NASA Technical Reports Server (NTRS)
Litt, Jonathan S.
2007-01-01
A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least-squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.
Edward Jero, S; Ramu, Palaniappan; Ramakrishnan, S
2014-10-01
ECG Steganography provides secured transmission of secret information such as patient personal information through ECG signals. This paper proposes an approach that uses discrete wavelet transform to decompose signals and singular value decomposition (SVD) to embed the secret information into the decomposed ECG signal. The novelty of the proposed method is to embed the watermark using SVD into the two dimensional (2D) ECG image. The embedding of secret information in a selected sub band of the decomposed ECG is achieved by replacing the singular values of the decomposed cover image by the singular values of the secret data. The performance assessment of the proposed approach allows understanding the suitable sub-band to hide secret data and the signal degradation that will affect diagnosability. Performance is measured using metrics like Kullback-Leibler divergence (KL), percentage residual difference (PRD), peak signal to noise ratio (PSNR) and bit error rate (BER). A dynamic location selection approach for embedding the singular values is also discussed. The proposed approach is demonstrated on a MIT-BIH database and the observations validate that HH is the ideal sub-band to hide data. It is also observed that the signal degradation (less than 0.6%) is very less in the proposed approach even with the secret data being as large as the sub band size. So, it does not affect the diagnosability and is reliable to transmit patient information.