The social mechanism of political deliberation and citizen participation in Guangdong China

Many studies have focused on why deliberative institutions should be established in order to develop Chinese people’s citizenry skills; however few focus on the social conditions and public sentiments that shape the development of deliberative mechanisms. Skills and awareness of citizenry is not only brought into being by deliberative institutions that are set up by the government, but evolve through interplays between technologies and social changes. As a test-bed for economic reform Guangdong is increasingly identified by translocality and hybrid culture. This is framed by identity conflict and unrests, much of which is due to soaring wealth polarisation, high volumes of population movement, cultural collisions and ongoing linguistic contestations. These unrests show the region’s transformation goes beyond the economic front. Profound changes are occurring at what anthropologists and philosophers call the changing social conciseness or moral landscape (Ci, 1994; Yan, 2010). The changing social moralities are a reflection of the awareness of individuals’ rights and responsibilities, and their interdependencies from dominant ideologies. This paper discusses Guangdong’s social and cultural characteristics, and questions how existing social conditions allow the staging of political deliberation by facilitating political engagement and the formation of public opinion. The paper will investigate the tragedy of Xiao Yueyue in Foshan, Guangdong, where ‘right’ and ‘responsibility’, ‘self’ and ‘other’ define the public sentiments of deliberation and participation.

The role of randomly mixed-layered chlorite/smectite in the transformation of smectite to chlorite

Vesicular and groundmass phyllosilicates in a hydrothermally altered basalt from the Point Sal ophiolite, California, have been studied using transmission electron microscopy (TEM). Pore-filling phyllosilicates are texturally characterized as having coherent, relatively thick and defect-free crystals of chlorite (14 Å) with occasional 24-Å periodicities. Groundmass phyllosilicates are texturally characterized as 1) randomly oriented crystals up to 200 Å in width and 2) larger, more coherent crystals up to 1000 Å in width. Small crystallites contain predominantly 14-Å layers with some 24-Å units. Large crystals show randomly interlayered chlorite/smectite (C/S), with approximately 50% chlorite on average. Adjacent smectite-like layers are not uncommon in the groundmass phyllosilicates. Electron microprobe analyses show that Fe/Mg ratios of both groundmass and vesicular phyllosilicates are fairly constant. Termination of brucite-like interlayers has been identified in some of the TEM images. The transformation mechanisms represented by these layer terminations are 1) growth of a brucite-like interlayer within smectite interlayer regions and 2) the dissolution and reprecipitation of elements to form chlorite layers. Both mechanisms require an increase in volume as smectite transforms to chlorite. The data, combined with that from previously published reports, suggest that randomly interlayered C/S is a metastable phase formed in microenvironments with low water/rock ratios. Chlorite forms in microenvironments in the same sample dominated by higher water/rock ratios. The relatively constant number of Mg's in the structure (Mg#) of both structures indicates that in both microenvironments the bulk rock composition has influence over the composition of phyllosilicates.

Accurate stratospheric particle-size distributions from a flat-plate collection surface

The first representative chemical, structural, and morphological analysis of the solid particles from a single collection surface has been performed. This collection surface sampled the stratosphere between 17 and 19km in altitude in the summer of 1981, and therefore before the 1982 eruptions of El Chichón. A particle collection surface was washed free of all particles with rinses of Freon and hexane, and the resulting wash was directed through a series of vertically stacked Nucleopore filters. The size cutoff for the solid particle collection process in the stratosphere is found to be considerably less than 1 μm. The total stratospheric number density of solid particles larger than 1μm in diameter at the collection time is calculated to be about 2.7×10−1 particles per cubic meter, of which approximately 95% are smaller than 5μm in diameter. Previous classification schemes are expanded to explicitly recognize low atomic number material. With the single exception of the calcium-aluminum-silicate (CAS) spheres all solid particle types show a logarithmic increase in number concentration with decreasing diameter. The aluminum-rich particles are unique in showing bimodal size distributions. In addition, spheres constitute only a minor fraction of the aluminum-rich material. About 2/3 of the particles examined were found to be shards of rhyolitic glass. This abundant volcanic material could not be correlated with any eruption plume known to have vented directly to the stratosphere. The micrometeorite number density calculated from this data set is 5×10−2 micrometeorites per cubic meter of air, an order of magnitude greater than the best previous estimate. At the collection altitude, the maximum collision frequency of solid particles >5μm in average diameter is calculated to be 6.91×10−16 collisions per second, which indicates negligible contamination of extraterrestrial particles in the stratosphere by solid anthropogenic particles.

Microanalysis of clays at low temperature

Accurate thin-film energy dispersive spectroscopic (EDS) analyses of clays with low-atomic-number (low Z) elements (e.g. Na, Al, Si), presents a challenge to the microscopist not only because of the spatial resolution required, but also because of their susceptibility to electron beam-induced radiation damange and very low X-ray count rates. Most common clays, such as kaolinite, smectite and illite occur as submicrometer crystallites with varying degrees of structural disorder in at least two directions and may have dimensions as small as one or two unit cells along the basal direction. Thus, even clays with relatively large a-b dimenstions (e.g., 100 x 100 nm) may be <5nm in the c-axis direction. For typical conditions in an analytical electron microscope (AEM), this sample thickness gives rise to very poor count rates (<200cps) and necessitates long counting times (>300s) in order to obtain satisfactory statistical precision. Unfortunately, beam damage rates for the common clays are very rapid (<10s in imaging mode) between 100kV and 200kV. With a focussed probe for elemental analyses, the damage rate is exacerbated by a high current density and may result in loss of low-Z elements during data collection and consequent loss of analytical accuracy.

High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations

The pioneering work of Runge and Kutta a hundred years ago has ultimately led to suites of sophisticated numerical methods suitable for solving complex systems of deterministic ordinary differential equations. However, in many modelling situations, the appropriate representation is a stochastic differential equation and here numerical methods are much less sophisticated. In this paper a very general class of stochastic Runge-Kutta methods is presented and much more efficient classes of explicit methods than previous extant methods are constructed. In particular, a method of strong order 2 with a deterministic component based on the classical Runge-Kutta method is constructed and some numerical results are presented to demonstrate the efficacy of this approach.

Order conditions of stochastic Runge-Kutta methods by B-series

In this paper, general order conditions and a global convergence proof are given for stochastic Runge Kutta methods applied to stochastic ordinary differential equations ( SODEs) of Stratonovich type. This work generalizes the ideas of B-series as applied to deterministic ordinary differential equations (ODEs) to the stochastic case and allows a completely general formalism for constructing high order stochastic methods, either explicit or implicit. Some numerical results will be given to illustrate this theory.

High strong order methods for non-commutative stochastic ordinary differential equation systems and the Magnus formula

In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

General order conditions for stochastic Runge-Kutta methods for both commuting and non-commuting stochastic ordinary differential equation systems

In many modeling situations in which parameter values can only be estimated or are subject to noise, the appropriate mathematical representation is a stochastic ordinary differential equation (SODE). However, unlike the deterministic case in which there are suites of sophisticated numerical methods, numerical methods for SODEs are much less sophisticated. Until a recent paper by K. Burrage and P.M. Burrage (1996), the highest strong order of a stochastic Runge-Kutta method was one. But K. Burrage and P.M. Burrage (1996) showed that by including additional random variable terms representing approximations to the higher order Stratonovich (or Ito) integrals, higher order methods could be constructed. However, this analysis applied only to the one Wiener process case. In this paper, it will be shown that in the multiple Wiener process case all known stochastic Runge-Kutta methods can suffer a severe order reduction if there is non-commutativity between the functions associated with the Wiener processes. Importantly, however, it is also suggested how this order can be repaired if certain commutator operators are included in the Runge-Kutta formulation. (C) 1998 Elsevier Science B.V. and IMACS. All rights reserved.

A bound on the maximum strong order of stochastic Runge-Kutta methods for stochastic ordinary differential equations

In Burrage and Burrage [1] it was shown that by introducing a very general formulation for stochastic Runge-Kutta methods, the previous strong order barrier of order one could be broken without having to use higher derivative terms. In particular, methods of strong order 1.5 were developed in which a Stratonovich integral of order one and one of order two were present in the formulation. In this present paper, general order results are proven about the maximum attainable strong order of these stochastic Runge-Kutta methods (SRKs) in terms of the order of the Stratonovich integrals appearing in the Runge-Kutta formulation. In particular, it will be shown that if an s-stage SRK contains Stratonovich integrals up to order p then the strong order of the SRK cannot exceed min{(p + 1)/2, (s - 1)/2), p greater than or equal to 2, s greater than or equal to 3 or 1 if p = 1.

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

The digital transformation of 21st century news journalism

This paper deals with the transformations that have occurred in news journalism worldwide in the early 21st century. I argue that they havebeen the most significant changes to the profession for 100 years, and the challenges facing the news media industry in responding to them are substantial, as are those facing journalism education. This argument is developed in relation to the crisis of the newspaper business model, and why social media, blogging and citizen journalism have not filled the gap left by the withdrawal of resources from traditional journalism. It also draws upon Wikileaks as a case study in debates about computational and data-driven journalism, and whether large-scale "leaks" of electronic documents may be the future of investigative journalism.

A framework for a dense matching algorithm : Results using matching metrics and order statistic filters

An algorithm for computing dense correspondences between images of a stereo pair or image sequence is presented. The algorithm can make use of both standard matching metrics and the rank and census filters, two filters based on order statistics which have been applied to the image matching problem. Their advantages include robustness to radiometric distortion and amenability to hardware implementation. Results obtained using both real stereo pairs and a synthetic stereo pair with ground truth were compared. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

Order statistic filters for image matching

The rank and census are two filters based on order statistics which have been applied to the image matching problem for stereo pairs. Advantages of these filters include their robustness to radiometric distortion and small amounts of random noise, and their amenability to hardware implementation. In this paper, a new matching algorithm is presented, which provides an overall framework for matching, and is used to compare the rank and census techniques with standard matching metrics. The algorithm was tested using both real stereo pairs and a synthetic pair with ground truth. The rank and census filters were shown to significantly improve performance in the case of radiometric distortion. In all cases, the results obtained were comparable to, if not better than, those obtained using standard matching metrics. Furthermore, the rank and census have the additional advantage that their computational overhead is less than these metrics. For all techniques tested, the difference between the results obtained for the synthetic stereo pair, and the ground truth results was small.

Supreme Court Act 1995 (Qld) s 253 – whether refusal to stay execution of costs is an order “as to costs only”

In Virgtel Ltd v Zabusky [2009] QCA 92 the Queensland Court of Appeal considered the scope of an order “as to costs only” within the meaning of s 253 of the Supreme Court Act 1995 (Qld) (‘the Act”). The Court also declined to accept submissions from one of the parties after oral hearing, and made some useful comments which serve as a reminder to practitioners of their obligations in that regard.