914 resultados para two-step chemical reaction model


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These are data of eddy covariance flux measurements of formic acid (HCOOH), performed by a chemical ionization mass spectrometer (CIMS) over a boreal forest canopy in Hyytiälä, Finland, in spring/summer 2014. Results from the 1-D chemical transport model runs using SOSAA (Simulate Organic vapours, Sulphuric Acid and Aerosols) are included as well. The data accompany a submission of a manuscript to Geophysical Research Letters for consideration for publication (Schobesberger et al.).

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A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

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A novel laponite RD clay-based Fe nanocomposite (Fe-Lap-RD) has been successfully synthesized through a reaction between a solution of iron salt and an aqueous dispersion of laponite RD clay. The X-ray diffraction (XRD) results reveal that the Fe-Lap-RD mainly consists of Fe2O3 (maghemite) and Fe2Si4O10(OH)2 (iron silicate hydroxide), which have tetragonal and monoclinic structures, respectively, and has a high specific surface area as well as a high pore volume. The photo-catalytic activity of the Fe-Lap-RD was examined in the photo-assisted degradation of an organic azo dye Orange II. It was found that the mineralization of Orange 11 undergoes a slower kinetics than discoloration, and 70% total organic carbon (TOC) of 0.2 mM Orange 11 can be removed in 90 min, implying that the Fe-Lap-RD exhibited a high photo-catalytic activity in the presence of H2O2 and UV light (254 nm) in the photo-assisted degradation of Orange II. In addition, our experiments also illustrate that the Fe-Lap-RD has a long-term stability but is of low cost. This study illustrates the possibility of photo-assisted degradation of organic compounds without the requirements to remove the Fe ions after reaction. Two possible catalytic reaction mechanisms are also proposed. (C) 2003 Elsevier Science Ltd. All rights reserved.

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The purpose of this analysis is threefold: first, to extract from the literature, current levels of GP detection of at-risk drinking by their patients, rates at which general practitioners (GPs) offer an intervention; and the effectiveness of these interventions; secondly, to develop a model based on this literature to be used in conjunction with scenario analysis; and thirdly, to consider the cost implications of current efforts and various scenarios. This study deals specifically with Australian general practice. A two-step procedure is used in the scenario analysis, which involves identifying opportunities for detection, intervention, effectiveness and assigning probabilities to outcomes. The results suggest that increasing rates of GP intervention achieves greatest benefit and return on resource use. For every 5% point increase in the rate of GP intervention, an additional 26 754 at-risk drinkers modify their drinking behaviour at a cost of $231.45 per patient. This compares with a cost per patient modifying drinking behaviour of $232.60 and $208.31 for every 5% point increase in the rates of detection and effectiveness, respectively. The knowledge, skill and attitude of practitioners toward drinking are significant, and they can be the prime motivators in persuading their patients to modify drinking behaviour.

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We investigate quantum many-body systems where all low-energy states are entangled. As a tool for quantifying such systems, we introduce the concept of the entanglement gap, which is the difference in energy between the ground-state energy and the minimum energy that a separable (unentangled) state may attain. If the energy of the system lies within the entanglement gap, the state of the system is guaranteed to be entangled. We find Hamiltonians that have the largest possible entanglement gap; for a system consisting of two interacting spin-1/2 subsystems, the Heisenberg antiferromagnet is one such example. We also introduce a related concept, the entanglement-gap temperature: the temperature below which the thermal state is certainly entangled, as witnessed by its energy. We give an example of a bipartite Hamiltonian with an arbitrarily high entanglement-gap temperature for fixed total energy range. For bipartite spin lattices we prove a theorem demonstrating that the entanglement gap necessarily decreases as the coordination number is increased. We investigate frustrated lattices and quantum phase transitions as physical phenomena that affect the entanglement gap.

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Research techniques and a methodology have been developed that enable the reduction kinetics of molten lead smelting slags with solid carbon to be studied. The rates of reduction of PbO-FeO-Fe2O3-CaO-SiO2 slags with carbon have been measured for a range of slag compositions for PbO concentrations between 3 and 100 weight percent, and temperatures between 1423 and 1573 K. The reduction rates were determined for both graphite and coke. Within the range of process conditions examined, it has been shown that the reaction rates are almost independent of carbon reactivity, SiO2/CaO and SiO2/Fe ratio in the range of compositions investigated and are not influenced by the presence of sulphur in the slag.The apparent first order rate constants for oxygen removal increase with increasing PbO concentration and oxygen activity in the slag. The data indicate that the rate limiting reaction step for the reduction of lead slags with solid carbon is the chemical reaction at the gas/slag interface.

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Entrainment in flotation can be considered as a two-step process, including the transfer of the suspended solids in the top of the pulp region just below the pulp-froth interface to the froth phase and the transfer of the entrained particles in the froth phase to the concentrate. Both steps have a strong classification characteristic. The degree of entrainment describes the classification effect of the drainage process in the froth phase. This paper briefly reviews two existing models of degree of entrainment. Experimental data were collected from an Outokumpu 3 m(3) tank cell in the Xstrata Mt. Isa Mines copper concentrator. The data are fitted to the models and the effect of cell operating conditions including air rate and froth height on the degree of entrainment is examined on a size-by-size basis. It is found that there is a strong correlation between the entrainment and the water recovery, which is close to lineal. for the fines. The degree of entrainment decreases with increase in particle size. Within the normal range of cell operating conditions, few particles coarser than 50 mu m are recovered by entrainment. In general, the degree of entrainment increases with increase in the ail rate and decreases with increase in the froth height. Air rate and froth height strongly interact with each other and affect the entrainment process mainly via changes in the froth retention time, the froth structure and froth properties. As a result, other mechanisms such as entrapment may become important in recovering the coarse entrained particles. (c) 2005 Elsevier Ltd. All rights reserved.

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Iodine-doped (I-doped) mesoporous titania with a bicrystalline (anatase and rutile) framework was synthesized by a two-step template hydrothermal synthesis route. I-doped titania with anatase structure was also synthesized without the use of a block copolymer as a template. The resultant titania samples were characterized by X-ray diffraction, Raman spectroscopy, Fourier transform infrared, nitrogen adsorption, transmission electron microscopy, X-ray photoelectron spectroscopy, and UV-visible absorption spectroscopy. Both I-doped titania samples, with and without template, show much better photocatalytic activity than commercial P25 titania in the photodegradation of methylene blue under the irradiation of visible light (> 420 nm) and UV-visible light. Furthermore, I-doped mesoporous titania with a bicrystalline framework exhibits better activity than I-doped titania with anatase structure. The effect of rutile phase in titania on the adsorptive capacity of water and surface hydroxyl, and photocatalytic activity was investigated in detail. The excellent performance of I-doped mesoporous titania under both visible light and UV-visible light can be attributed to the combined effects of bicrystalline framework, high crystallinity, large surface area, mesoporous structure, and high visible light absorption induced by I-doping.

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Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

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We present a machine learning model that predicts a structural disruption score from a protein’s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision. ©2005 IEEE

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The chemical industry in China is facing fierce competition and exposure to market forces as a result of changes in the country's economic policy. The Chinese government has applied administrative actions rather than simply relying on market forces to address the changing dynamics. It has attempted to privatise state-owned chemical enterprises (SOCEs) by corporatisation, coupled with industrial restructuring by merging individual state-owned enterprises into groups. Based on a quantitative survey in combination with case studies of two Chinese chemical enterprises, this paper concludes that in this industry building competences is more effective than privatisation and restructuring to improve performance.

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There is an increasing need of a model for the process-based performance measurement of multispecialty tertiary care hospitals for quality improvement. Analytic hierarchy process (AHP) is utilized in this study to evolve such a model. Each step in the model was derived by group-discussions and brainstorming sessions among experienced clinicians and managers. This tool was applied to two tertiary care teaching hospitals in Barbados and India. The model enabled identification of specific areas where neither hospital performed very well, and helped to suggest recommendations to improve those areas. AHP is recommended as a valuable tool to measure the process-based performance of multispecialty tertiary care hospitals. © Emerald Group Publishing Limited.

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Adapting to blurred images makes in-focus images look too sharp, and vice-versa (Webster et al, 2002 Nature Neuroscience 5 839 - 840). We asked how such blur adaptation is related to contrast adaptation. Georgeson (1985 Spatial Vision 1 103 - 112) found that grating contrast adaptation followed a subtractive rule: perceived (matched) contrast of a grating was fairly well predicted by subtracting some fraction k(~0.3) of the adapting contrast from the test contrast. Here we apply that rule to the responses of a set of spatial filters at different scales and orientations. Blur is encoded by the pattern of filter response magnitudes over scale. We tested two versions - the 'norm model' and 'fatigue model' - against blur-matching data obtained after adaptation to sharpened, in-focus or blurred images. In the fatigue model, filter responses are simply reduced by exposure to the adapter. In the norm model, (a) the visual system is pre-adapted to a focused world and (b) discrepancy between observed and expected responses to the experimental adapter leads to additional reduction (or enhancement) of filter responses during experimental adaptation. The two models are closely related, but only the norm model gave a satisfactory account of results across the four experiments analysed, with one free parameter k. This model implies that the visual system is pre-adapted to focused images, that adapting to in-focus or blank images produces no change in adaptation, and that adapting to sharpened or blurred images changes the state of adaptation, leading to changes in perceived blur or sharpness.