Gauge P-representations for quantum-dynamical problems: Removal of boundary terms

P-representation techniques, which have been very successful in quantum optics and in other fields, are also useful for general bosonic quantum-dynamical many-body calculations such as Bose-Einstein condensation. We introduce a representation called the gauge P representation, which greatly widens the range of tractable problems. Our treatment results in an infinite set of possible time evolution equations, depending on arbitrary gauge functions that can be optimized for a given quantum system. In some cases, previous methods can give erroneous results, due to the usual assumption of vanishing boundary conditions being invalid for those particular systems. Solutions are given to this boundary-term problem for all the cases where it is known to occur: two-photon absorption and the single-mode laser. We also provide some brief guidelines on how to apply the stochastic gauge method to other systems in general, quantify the freedom of choice in the resulting equations, and make a comparison to related recent developments.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

The kinetics of NO and N2O reduction over coal chars in fluidised-bed combustion

This paper presents a comprehensive and critical review of the mechanisms and kinetics of NO and N2O reduction reaction with coal chars under fluidised-bed combustion conditions (FBC). The heterogeneous reactions of NO and N2O with char/carbon surface have been well recognised as the most important processes in reducing both NOx and N2O in situ FBC. Compared to NO-carbon reactions in FBC, the reactions of N2O with chars have been relatively less understood and studied. Beginning with the overall reaction schemes for both NO and N2O reduction, the paper extensively discusses the reaction mechanisms including the effects of active surface sites. Generally, NO- and N2O-carbon reactions follow a series of step reactions. However, questions remain concerning the role of adsorbed phases of NO and N2O, and the behaviour of different surface sites. Important kinetics factors such as the rate expressions, kinetics parameters as well as the effects of surface area and pore structure are discussed in detail. The main factors influencing the reduction of NO and N2O in FBC conditions are the chemical and physical properties of chars, and the operating parameters of FBC such as temperature, presence of CO, O-2 and pressure. It is shown that under similar conditions, N2O is more readily reduced on the char surface than NO. Temperature was found to be a very important parameter in both NO and N2O reduction. It is generally agreed that both NO- and N2O-carbon reactions follow first-order reaction kinetics with respect to the NO and N2O concentrations. The kinetic parameters for NO and N2O reduction largely depend on the pore structure of chars. The correlation between the char surface area and the reactivities of NO/N2O-char reactions is considered to be of great importance to the determination of the reaction kinetics. The rate of NO reduction by chars is strongly enhanced by the presence of CO and O-2, but these species may not have significant effects on the rate of N2O reduction. However, the presence of these gases in FBC presents difficulties in the study of kinetics since CO cannot be easily eliminated from the carbon surface. In N2O reduction reactions, ash in chars is found to have significant catalytic effects, which must be accounted for in the kinetic models and data evaluation. (C) 1997 Elsevier Science Ltd.

Thermogravimetric determination of the carbon dioxide reactivity of char from some New Zealand coals and its association with the inorganic geochemistry of the parent coal

Thermogravimetrically-determined carbon dioxide reactivities of chars formed from New Zealand coals, ranging in rank from lignite to high volatile bituminous, vary from 0.12 to 10.63 mg/h/mg on a dry, ash-free basis. The lowest rank subbituminous coal chars have similar reactivities to the lignite coal chars. Calcium content of the char shows the strongest correlation with reactivity, which increases as the calcium content increases. High calcium per se does not directly imply a high char reactivity. Organically-bound calcium catalyses the conversion of carbon to carbon monoxide in the presence of carbon dioxide, whereas calcium present as discrete minerals in the coal matrix, e.g., calcite, fails to significantly affect reactivity. Catalytic effects of magnesium, iron, sodium and phosphorous are not as obvious, but can be recognised for individual chars. The thermogravimetric technique provides a fast, reliable analysis that is able to distinguish char reactivity differences between coals, which may be due to any of the above effects. Published by Elsevier Science B.V.

Coalbed methane sorption related to coal composition

Gas sorption by coal is closely related to its physical and chemical properties, which are, in turn, governed by coal type and rank. The role of coal type (sensu maceral composition) is not fully established but it is clear that coal type may affect both adsorption capacity and desorption rate. Adsorption capacity is closely related to micropore (pores <2 nm) development, which is rank and maceral dependent. Adsorption isotherms indicate that in most cases bright (vitrinite-rich) coals have a greater adsorption capacity than their dull (often inertinite-rich) equivalents. However, no differences, or even the opposing trend, may be observed in relation to coal type. Desorption rate investigations have been performed using selected bright and dull coal samples in a high pressure microbalance. Interpretation of results using unipore spherical and bidisperse pore models indicate the importance of the pore structure. Bright, vitrinite-rich coals usually have the slowest desorption rates which is associated with their highly microporous structure. However, rapid desorption in bright coals may be related to development of extensive, unmineralised fracture systems. Both macro-and micro-pore systems are implicated in the more rapidly desorbing dull coals. Some dull, inertinite-rich coals may rapidly desorb due to a predominance of large, open cell lumina. Mineral matter is essentially nonadsorbent to coal gases and acts as a simple diluent. However, mineral-rich coals may be associated with more rapid desorption. Coal rank and type (maceral composition) per se do not appear to be the critical factors in controlling gas sorption, but rather the influence they exert over pore structure development. (C) 1998 Elsevier Science B.V.

VOC removal: Comparison of MCM-41 with hydrophobic zeolites and activated carbon

The recently discovered mesoporous molecular sieve MCM-41 was tested as an adsorbent for VOC removal. Its adsorption/desorption properties were evaluated and compared with other hydrophobic zeolites (silicalite-1 and zeolite Y) and a commercial activated carbon, BPL. The adsorption isotherms of some typical VOCs (benzene, carbon tetrachloride, and n-hexane) on MCM-41 are of type IV according to the IUPAC classification, drastically different from the other microporous adsorbents, indicating that VOCs, in the gas phase, have to be at high partial pressures in order to make the most of the new mesoporous material as an adsorbent for VOC removal. However, a proper modification of the pore openings of MCM-41 can change the isotherm types from type IV to type I without remarkable loss of the accessible pare volumes and, therefore, significantly enhance the adsorption performance at low partial pressures. Adsorption isotherms of water on these adsorbents are all of type V, demonstrating that they possess a similar hydrophobicity. Desorption of VOCs from MCM-41 could be achieved at lower temperatures (50-60 degrees C), while this had to be conducted at higher temperatures (100-120 degrees C) for microporous adsorbents, zeolites, and activated carbons.

Adsorption characteristics of phenolic compounds onto coal-reject-derived adsorbents

Carbonaceous adsorbents were prepared by heat treatment of coal reject at 600 degrees C, after chemical treatment in HNO3, H2SO4, and NaOH at 25 and 75 degrees C. Pore structure characterization and the phenol adsorption capacities of the adsorbents showed that nitric acid pretreatment significantly enhanced the surface properties, consequently the adsorption capacities of the adsorbents. A number of samples were subsequently prepared by carbonizing coal reject at 600 degrees C, after pretreatment in HNO3 under various conditions. The acid concentration, residence time, and reaction temperature were varied to obtain adsorbents with various pore structures. The adsorption capacities of the derived adsorbents for phenol, p-nitrophenol, and benzene were measured to gain further insights into the pore structure evolution. Adsorption isotherms of phenol, p-nitrophenol, and p-chlorophenol on the best adsorbent prepared were determined and correlated with theoretical isotherm equations, such as the Langmuir, Freundlich, and Redlich-Peterson equations.

Knowledge discovery and data mining in biological databases

The new technologies for Knowledge Discovery from Databases (KDD) and data mining promise to bring new insights into a voluminous growing amount of biological data. KDD technology is complementary to laboratory experimentation and helps speed up biological research. This article contains an introduction to KDD, a review of data mining tools, and their biological applications. We discuss the domain concepts related to biological data and databases, as well as current KDD and data mining developments in biology.

Coupled experimental and thermodynamic modeling studies for metallurgical smelting and coal combustion slag systems

An extensive research program focused on the characterization of various metallurgical complex smelting and coal combustion slags is being undertaken. The research combines both experimental and thermodynamic modeling studies. The approach is illustrated by work on the PbO-ZnO-Al2O3-FeO-Fe2O3-CaO-SiO2 system. Experimental measurements of the liquidus and solidus have been undertaken under oxidizing and reducing conditions using equilibration, quenching, and electron probe X-ray microanalysis. The experimental program has been planned so as to obtain data for thermodynamic model development as well as for pseudo-ternary Liquidus diagrams that can be used directly by process operators. Thermodynamic modeling has been carried out using the computer system FACT, which contains thermodynamic databases with over 5000 compounds and evaluated solution models. The FACT package is used for the calculation of multiphase equilibria in multicomponent systems of industrial interest. A modified quasi-chemical solution model is used for the liquid slag phase. New optimizations have been carried out, which significantly improve the accuracy of the thermodynamic models for lead/zinc smelting and coal combustion processes. Examples of experimentally determined and calculated liquidus diagrams are presented. These examples provide information of direct relevance to various metallurgical smelting and coal combustion processes.

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.

Petrographic and isotope constraints on the origin of authigenic carbonate minerals and the associated fluid evolution in Late Permian coal measures, Bowen Basin (Queensland), Australia

Authigenic carbonate minerals are ubiquitous throughout the Late Permian coal measures of the Bowen Basin, Queensland, Australia. In the northern Bowen Basin, carbonates include the following assemblages: siderite I (delta O-18(SMOW) = +11.4 to + 17%, delta C-13(PDB) = - 5.3 to + 120), Fe-Mg calcite-ankerite-siderite II mineral association (delta O-18(SMOW) = +7.2 to + 10.20, delta C-13(PDB) = 10.9 to - 1.80 for ankerite) and a later calcite (delta O-18(SMOW) = +5.9 to + 14.60, delta C-13(PDB) = -11.4 to + 4.40). In the southern Bowen Basin, the carbonate phase consists only of calcite (delta O-18(SMOW) = +12.5 to + 14.80, delta C-13(PDB) = -19.4 to + 0.80), where it occurs extensively throughout all stratigraphic levels. Siderite I occurs in mudrocks and sandstones and predates all other carbonate minerals. This carbonate phase is interpreted to have formed as an early diagenetic mineral from meteoric waters under cold climate and reducing conditions. Fe-Mg calcite-ankerite-siderite Il occur in sandstones as replacement of volcanic rock fragments. Clay minerals (illite-smectite, chlorite and kaolinite) postdate Ca-Fe-Mg carbonates, and precipitation of the later calcite is associated with clay mineral formation. The Ca-Fe-Mg carbonates and later calcite of the northern Bowen Basin are regarded as having formed as a result of hydrothermal activity during the latest Triassic extensional tectonic event which affected this part of the basin, rather than deep burial diagenesis during the Middle to Late Triassic as previously reported. This hypothesis is based on the timing relationships of the authigenic mineral phases and the low delta O-18 values of ankerite and calcite, together with radiometric dating of illitic clays and recently published regional geological evidence. Following the precipitation of the Ca-Fe-Mg carbonates from strongly O-18-depleted meteoric-hydrothermal fluids, continuing fluid circulation and water-rock interaction resulted in dissolution of these carbonate phases as well as labile fragments of volcaniclastic rocks. Subsequently, the later calcite and day minerals precipitated from relatively evolved (O-18-enriched) fluids. The nearly uniform delta O-18 values of the southern Bowen Basin calcite have been attributed to very low water/rock ratio in the system, where the fluid isotropic composition was buffered by the delta O-18 values of rocks. (C) 2000 Elsevier Science B.V. All rights reserved.

Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

Removal of a cysteine ligand from rubredoxin: assembly of Fe2S2 and Fe(S-Cys)(3)(OH) centres

The electron transfer protein rubredoxin from Clostridium pasteurianum contains an Fe(S-Cys)(4) active site. Mutant proteins C9G, C9A, C42G and C42A, in which cysteine ligands are replaced by non-ligating Gly or Ala residues, have been expressed in Escherichia coli. The C42A protein expresses with a (Fe2S2)-S-III cluster in place. In contrast, the other proteins are isolated in colourless forms, although a (Fe2S2)-S-III cluster may be assembled in the C42G protein via incubation with Fe-III and sulfide. The four mutant proteins were isolated as stable mononuclear Hg-II forms which were converted to unstable mononuclear Fe-III preparations that contain both holo and apo protein. The Fe-III systems were characterized by metal analysis and mass spectrometry and by electronic, electron paramagnetic resonance, X-ray absorption and resonance Raman spectroscopies. The dominant Fe-III form in the C9A preparation is a Fe(S-Cys)(3)(OH) centre, similar to that observed previously in the C6S mutant protein. Related centres are present in the proteins NifU and IscU responsible for assembly and repair of iron-sulfur clusters in both prokaryotic and eukaryotic cells. In addition to Fe(S-Cys)(3)(OH) centres, the C9G, C42G and C42A preparations contain a second four-coordinate Fe-III form in which a ligand appears to be supplied by the protein chain. Electronic supplementary material to this paper can be obtained by using the Springer Link server located at http://dx.doi.org/10.1007/s00775-0020355-1.