Rural lines of flight: Telecommunications and post-metro dreaming

Information and communications technologies hold a prominent place in the cultural imagination of many people living outside the Australian metropolis, especially recent émigrés. A vision of a wired pastoral conjures up the possibilities of city work, connections and pleasures accompanying the flight to the country. Such aspirations have given a twist to one of the great topos of Australian post-invasion communications history, communications ameliorating the perceived isolation in the bush. This article examines important changes to rural telecommunications in the 1990s coinciding with post-metro dreaming and digital convergence, namely the rise of local telecommunications. Neo-Foucauldian accounts of citizenship hold some promise for explaining the criss-cross of tangled lines of flight in regional communications in the twenty-first century: emergent subjectivities, utopian digital modes of becoming, new politics of infrastructure, reconfigured relationships among state, market and citizen.

Existence of solutions for p(x)-Laplacian problems on a bounded domain

In this paper we study the following p(x)-Laplacian problem: -div(a(x)&VERBAR;&DEL; u&VERBAR;(p(x)-2)&DEL; u)+b(x)&VERBAR; u&VERBAR;(p(x)-2)u = f(x, u), x ε &UOmega;, u = 0, on &PARTIAL; &UOmega;, where 1< p(1) &LE; p(x) &LE; p(2) < n, &UOmega; &SUB; R-n is a bounded domain and applying the mountain pass theorem we obtain the existence of solutions in W-0(1,p(x)) for the p(x)-Laplacian problems in the superlinear and sublinear cases. © 2004 Elsevier Inc. All rights reserved.

A class of self-stabilizing MCA learning algorithms

In this letter, we propose a class of self-stabilizing learning algorithms for minor component analysis (MCA), which includes a few well-known MCA learning algorithms. Self-stabilizing means that the sign of the weight vector length change is independent of the presented input vector. For these algorithms, rigorous global convergence proof is given and the convergence rate is also discussed. By combining the positive properties of these algorithms, a new learning algorithm is proposed which can improve the performance. Simulations are employed to confirm our theoretical results.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

True measures of GDP and convergence

Widely used ''purchasing power parity'' comparisons of per capita GDP are not true quantity indexes and are subject to systematic substitution bins. This bias may distort measurement of convergence and divergence. Extending Varian's nonparametric construction of a true index gives the set of true indexes, including the new Ideal Afriat Index. These indexes are utility-consistent and independent of arbitrary reference price vectors. We establish bounds on the dispersion of true multilateral indexes, hence bounds on convergence. International price indexes understate both true GDP dispersion and, where prices are converging over time, the rate of true quantity convergence.

Sorting and convergence of primary olfactory axons are independent of the olfactory bulb

Primary olfactory axons expressing the same odorant receptor gene sort out and converge to fixed sites in the olfactory bulb. We examined the guidance of axons expressing the P2 odorant receptor when they were challenged with different cellular environments in vivo. In the mutant extratoes mouse, the olfactory bulb is lacking and is replaced by a fibrocellular mass. In these animals, primary olfactory axons form glomerular-like loci despite the absence of normal postsynaptic targets. P2 axons are able to sort out from other axons in this fibrocellular mass and converge to form loci of like axons. The sites of these loci along mediolateral and ventrodorsal axes were highly variable. Similar convergence was observed for larger subpopulations of axons expressing the same cell surface carbohydrates. The sorting out and convergence of like axons also occurred during regeneration following bulbectomy. Olfactory axon behaviour in these models demonstrates that sorting and convergence of axons are independent of the target, which instead provides distinct topographic cues for guidance. (C) 2003 Wiley-Liss, Inc.

The highly rearranged mitochondrial genome of the plague thrips, Thrips imaginis (Insecta : thysanoptera): Convergence of two novel gene boundaries and an extraordinary arrangement of rRNA genes

To help understand the mechanisms of gene rearrangement in the mitochondrial (mt) genomes of hemipteroid insects, we sequenced the mt genome of the plague thrips, Thrips imaginis (Thysanoptera). This genome is circular, 15,407 by long, and has many unusual features, including (1) rRNA genes inverted and distant from one another, (2) an extra gene for tRNA-Ser, (3) a tRNA-Val lacking a D-arm, (4) two pseudo-tRNA genes, (5) duplicate control regions, and (6) translocations and/or inversions of 24 of the 37 genes. The mechanism of rRNA gene transcription in T. imaginis may be different from that of other arthropods since the two rRNA genes have inverted and are distant from one another. Further, the rRNA genes are not adjacent or even close to either of the two control regions. Tandem duplication and deletion is a plausible model for the evolution of duplicate control regions and for the gene translocations, but intramitochondrial recombination may account for the gene inversions in T. imaginis. All the 18 genes between control regions #1 and #2 have translocated and/or inverted, whereas only six of the 20 genes outside this region have translocated and/or inverted. Moreover, the extra tRNA gene and the two pseudo-tRNA genes are either in this region or immediately adjacent to one of the control regions. These observations suggest that tandem duplication and deletion may be facilitated by the duplicate control regions and may have occurred a number of times in the lineage leading to T. imaginis. T. imaginis shares two novel gene boundaries with a lepidopsocid species from another order of hemipteroid insects, the Psocoptera. The evidence available suggests that these shared gene boundaries evolved by convergence and thus are not informative for the interordinal phylogeny of hemipteroid insects. We discuss the potential of hemipteroid insects as a model system for studies of the evolution of animal rut genomes and outline some fundamental questions that may be addressed with this system.

Income Ranking and convergence with physical and human capital and income equality

This paper presents an overlapping generations model with physical and human capital and income inequality. It shows that inequality impedes output growth by directly harming capital accumulation and indirectly raising the ratio of physical to human capital. The convergence speed of output growth equals the lower of the convergence speeds of the relative capital ratio and inequality, and varies with initial states. Among economies with the same balanced growth rate but different initial income levels, the ranking of income can switch in favor of those starting from low inequality and a low ratio of physical to human capital, particularly if the growth rate converges slowly. (C) 2004 Elsevier B.V. All rights reserved.

Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.