Estimating economic relationships subject to firm- and time-varying equality and inequality constraints

Applied econometricians often fail to impose economic regularity constraints in the exact form economic theory prescribes. We show how the Singular Value Decomposition (SVD) Theorem and Markov Chain Monte Carlo (MCMC) methods can be used to rigorously impose time- and firm-varying equality and inequality constraints. To illustrate the technique we estimate a system of translog input demand functions subject to all the constraints implied by economic theory, including observation-varying symmetry and concavity constraints. Results are presented in the form of characteristics of the estimated posterior distributions of functions of the parameters. Copyright (C) 2001 John Wiley Sons, Ltd.

Valuing ecological functions of biodiversity in changbaishan mountain biosphere reserve in northeast china

Conservation of biodiversity can generate considerable indirect economic value and this is being increasingly recognized in China. For a forest ecosystem type of a nature reserve, the most important of its values are its ecological functions which provide human beings and other living things with beneficial environmental services. These services include water conservancy, soil protection, CO2 fixation and O-2 release, nutrient cycling, pollutant decomposition, and disease and pest control. Based on a case study in Changbaishan Mountain Biosphere Reserve in Northeast China, this paper provides a monetary valuation of these services by using opportunity cost and alternative cost methods. Using such an approach, this reserve is valued at 510.11 million yuan (USD 61.68 mill.) per year, 10 times higher than the opportunity cost (51.78 mill. yuan/ha.a) for regular timber production. While China has heeded United Nations Environmental Program (UNEP)'s call for economic evaluation of ecological functions, the assessment techniques used need to be improved in China and in the West for reasons mentioned.

Sequestration of carbon by soil

Soil carbon is a major component of the terrestrial carbon cycle. The soils of the world contain more carbon than the combined total amounts occurring in vegetation and the atmosphere. Consequently, soils are a major reservoir of carbon and an important sink. Because of the relatively long period of time that carbon spends within the soil and is thereby withheld from the atmosphere, it is often referred to as being sequestered. Increasing the capacity of soils to sequester C provides a partial, medium-term countermeasure to help ameliorate the increasing CO2 levels in the atmosphere arising from fossil fuel burning and land clearing. Such action will also help to alleviate the environmental impacts arising from increasing levels of atmospheric CO2. The C sequestration potential of any soil depends on its capacity to store resistant plant components in the medium term and to protect and accumulate the humic substances (HS) formed from the transformations or organic materials in the soil environment. The sequestration potential of a soil depends on the vegetation it supports, its mineralogical composition, the depth of the solum, soil drainage, the availability of water and air, and the temperature of the soil environment. The sequestration potential also depends on the chemical characteristics of the soil organic matter and its ability to resist microbial decomposition. When accurate information for these features is incorporated in model systems, the potentials of different soils to sequester C can be reliably predicted. It is encouraging to know that improved soil and crop management systems now allow field yields to be maintained and soil C reserves to be increased, even for soils with depleted levels of soil C. Estimates of the soil C sequestration potential are discussed. Inevitably HS are the major components of the additionally sequestered C. It will be important to know more about the compositions and associations of these substances in the soil if we are able to predict reasonably accurately the ability of any soil type to sequester C in different cropping and soil management systems.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

Linear ketenimines. Variable structures of C,C-dicyanoketenimines and C,C-bis-sulfonylketenimines

C,C-Dicyanoketenimines 10a-c were generated by flash vacuum thermolysis of ketene NS-acetals 9a-c or by thermal or photochemical decomposition of alpha-azido-,beta-cyanocinnamonitrile 11. In the latter reaction, 3,3-dicyano-2-phenyl-1-azirine 12 is also formed. IR spectroscopy of the keteniminines isolated in Ar matrixes or as neat films, NMR spectroscopy of 10c, and theoretical calculations (B3LYP/6-31G*) demonstrate that these ketenimines have variable geometry, being essentially linear along the CCN-R framework in polar media (neat films and solution), but in the gas phase or Ar matrix they are bent, as is usual for ketenimines. Experiments and calculations agree that a single CN substituent as in 13 is not enough to enforce linearity, and sulfonyl groups are less effective that cyano groups in causing linearity. C,C-Bis(methylsulfonyl)ketenimines 4-5 and a C-cyano-C-(methylsulfonyl)ketenimine 15 are not linear. The compound p-O2NC6H4N=C= C(COOMe)2 previously reported in the literature is probably somewhat linearized along the CCNR moiety. A computational survey (B3LYP/6-31G*) of the inversion barrier at nitrogen indicates that electronegative C-substituents dramatically lower the barrier; this is also true of N-acyl substituents. Increasing polarity causes lower barriers. Although N-alkylbis(methylsulfonyl)ketenimines are not calculated to be linear, the barriers are so low that crystal lattice forces can induce planarity in N-methylbis(methylsulfonyl)ketenimine 3.

Productivity growth in Australian manufacturing sector: some new evidence

This article examines the productivity performance of Australia's manufacturing sector by decomposing its output growth into input growth, technological progress and gains in technical efficiency. This three-way decomposition is done with an improved version of the stochastic frontier model using eight, two-digit industry level data from 1968/9 to 1994/5. Empirical evidence shows that input growth fueled output growth from 1968/9 to 1973/4, but since then, total factor productivity (TFP) growth has been the main contributor of output growth. While the trend of TFP growth was found to be promising for most industries with positive and increasing technological progress, the negative gains from technical efficiency over time is however cause for concern.

Further decompositions of complete tripartite graphs into 5-cycles

Let K(r,s,t) denote the complete tripartite graph with partite sets of sizes r, s and t, where r less than or equal to s less than or equal to t. Necessary and sufficient conditions are given for decomposability of K(r, s, t) into 5-cycles whenever r, s and t are all even. This extends work done by Mahmoodian and Mirza-khani (Decomposition of complete tripartite graphs into 5-cycles, in: Combinatorics Advances, Kluwer Academic Publishers, Netherlands, 1995, pp. 235-241) and Cavenagh and Billington. (C) 2002 Elsevier Science B.V. All rights reserved.

Hydrofluoric acid pre-treatment for improving 13C CPMAS NMR spectral quality of forest soils in south-east Queensland, Australia

Hydrofluoric acid (HF) was used to pre-treat forest soils of south-east Queensland for assessing the effectiveness of iron (Fe) removal, carbon (C) composition using C-13 cross-polarisation (CP) with magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) before and after the HF pre-treatment, and the improvement of C-13 CPMAS NMR spectra. Soil samples were collected from 4 experimental sites of different soil types, harvest residue management or prescribed burning, and tree species. More than 86% of Fe was in all soil types removed by the HF treatment. The C-13 NMR spectral quality was improved with increased resolution, especially in the alkyl C and O-alkyl C regions, and reduced NMR run-time (1-5 h per sample compared with >20 h per sample without the pre-treatment). The C composition appeared to alter slightly after the pre-treatment, but this might be largely due to improved spectrometer conditions and increased resolution leading to more accurate NMR spectral integration. Organic C recovery after HF pre-treatment varied with soil types and forest management, and soluble soil organic matter (SOM) could be lost during the pre-treatment. The Fourier Transform-Infrared (FT-IR) spectra of HF extracts indicated the preferential removal of carboxylic C groups during the pre-treatment, but this could also be due to adsorbed water on the mineral matter. The NMR spectra revealed some changes in C composition and quality due to residue management and decomposition. Overall, the HF treatment was a useful pre-treatment for obtaining semi-quantitative C-13 CPMAS NMR spectra of subtropical Australian forest soils.

Impact of land-use on soil organic matter quality in south-western Australia - characterization with C-13 CP/MAS NMR spectroscopy

The influence of change in land-use from native vegetation to pasture (20-71 yr after conversion), and subsequent change from pasture to eucalypt plantation (7-10 yr after conversion) on soil organic matter quality was investigated using C-13 CP/MAS NMR spectroscopy. We studied surface soil (0-10 cm) from six sites representing a range of soil, and climate types from south-western Australia. Total C in the samples ranged from 1.6 to 5.5%, but the relative proportions of the four primary spectral regions (alkyl, O-alkyl, aromatic and carboxylic) were similar across the sites, and changes due to land-use at each site were relatively minor. Main impacts of changed land-use were higher O-alkyl (carbohydrate) material under pasture than under native vegetation and plantation (P = 0.048), and lower aromatic C under pasture than under native vegetation (P = 0.027). The decrease in aromatic C in pasture soils was related to time since clearing. (C) 2002 Elsevier Science Ltd. All rights reserved.

Conditional simulation of random fields by successive residuals

This paper presents a new approach to the LU decomposition method for the simulation of stationary and ergodic random fields. The approach overcomes the size limitations of LU and is suitable for any size simulation. The proposed approach can facilitate fast updating of generated realizations with new data, when appropriate, without repeating the full simulation process. Based on a novel column partitioning of the L matrix, expressed in terms of successive conditional covariance matrices, the approach presented here demonstrates that LU simulation is equivalent to the successive solution of kriging residual estimates plus random terms. Consequently, it can be used for the LU decomposition of matrices of any size. The simulation approach is termed conditional simulation by successive residuals as at each step, a small set (group) of random variables is simulated with a LU decomposition of a matrix of updated conditional covariance of residuals. The simulated group is then used to estimate residuals without the need to solve large systems of equations.

Conceptual modelling and ontology: Possibilities and pitfalls

Conceptual modelling is an activity undertaken during information systems development work to build a representation of selected semantics about some real-world domain. Ontological theories have been developed to account for the structure and behavior of the real world in general. In this paper, I discuss why ontological theories can be used to inform conceptual modelling research, practice, and pedagogy. I provide examples from my research to illustrate how a particular ontological theory has enabled me to improve my understanding of certain conceptual modelling practices and grammars. I describe, also, how some colleagues and I have used this theory to generate several counter-intuitive, sometimes surprising predictions about widely advocated conceptual modelling practices - predictions that subsequently were supported in empirical research we undertook. Finally, I discuss several possibilities and pitfalls I perceived to be associated with our using ontological theories to underpin research on conceptual modelling.

Composition and quality of harvest residues and soil organic matter under windrow residue management in young hoop pine plantations as revealed by solid-state C-13 NMR spectroscopy

Solid-state C-13 nuclear magnetic resonance (NMR) with cross-polarisation (CP) and magic-angle-spinning (MAS) was used to: (a) examine the changes in carbon (C) composition of windrowed harvest residues during the first 3 years of hoop pine plantations in subtropical Australia; (b) assess the impacts of windrowed harvest residues on soil organic matter (SOM) composition and quality in the 0-10 cm soil layer. Harvest residues were collected from 0-, 1-, 2- and 3-year-old windrows of ca. 2.5 m width (15 m apart for 0-, 1- and 2-year-old sites and 10 m apart for 3-year-old site). Soils from the 0 to 10 cm soil layer were collected from the 1-, 2- and 3-year-old sites. The 13C NMR spectra of the harvest residues indicated the presence of lignin in the hoop pine wood, foliage and newly incorporated organic matter (NIOM). Condensed tannin structures were found in the decay-resistant bark, small wood and foliage, but were absent in other residue components and SOM. The NMR spectra of small wood samples contained condensed tannin structures because the outer layer of bark was not removed. NIOM showed a shift from foliage-like structures (celluloses) to lignin-type structures, indicating an incorporation of woody residues from the decomposing harvest residues. Suberins were also present in the small wood, foliage and bark. The 13C CP NMR spectra of SOM indicated that in areas where windrows were present, SOM did not show compositional changes. However, an increase in SOM quality under the windrows in the second year after their formation as characterised by the alkyl C/O-alkyl C (A/O-A) ratio was mainly due to inputs from the decomposition of the labile, readily available components of the windrowed harvest residues. (C) 2002 Published by Elsevier Science B.V.

Fast, scalable master equation solution algorithms. IV. Lanczos iteration with diffusion approximation preconditioned iterative inversion

In this paper we propose a second linearly scalable method for solving large master equations arising in the context of gas-phase reactive systems. The new method is based on the well-known shift-invert Lanczos iteration using the GMRES iteration preconditioned using the diffusion approximation to the master equation to provide the inverse of the master equation matrix. In this way we avoid the cubic scaling of traditional master equation solution methods while maintaining the speed of a partial spectral decomposition. The method is tested using a master equation modeling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long-lived isomerizing intermediates. (C) 2003 American Institute of Physics.

Fast, scalable master equation solution algorithms. III. Direct time propagation accelerated by a diffusion approximation preconditioned iterative solver

In this paper we propose a novel fast and linearly scalable method for solving master equations arising in the context of gas-phase reactive systems, based on an existent stiff ordinary differential equation integrator. The required solution of a linear system involving the Jacobian matrix is achieved using the GMRES iteration preconditioned using the diffusion approximation to the master equation. In this way we avoid the cubic scaling of traditional master equation solution methods and maintain the low temperature robustness of numerical integration. The method is tested using a master equation modelling the formation of propargyl from the reaction of singlet methylene with acetylene, proceeding through long lived isomerizing intermediates. (C) 2003 American Institute of Physics.

Selecting methods to solve multi-well master equations

There are several competing methods commonly used to solve energy grained master equations describing gas-phase reactive systems. When it comes to selecting an appropriate method for any particular problem, there is little guidance in the literature. In this paper we directly compare several variants of spectral and numerical integration methods from the point of view of computer time required to calculate the solution and the range of temperature and pressure conditions under which the methods are successful. The test case used in the comparison is an important reaction in combustion chemistry and incorporates reversible and irreversible bimolecular reaction steps as well as isomerizations between multiple unimolecular species. While the numerical integration of the ODE with a stiff ODE integrator is not the fastest method overall, it is the fastest method applicable to all conditions.