Enclosures and Dichotomies: Coexistence vs. Distance in the Poems of John Clare

John Clare’s poetry emphasizes an affinity with environment by suspending the distinction between the inside (subject) and the outside (object). Clare’s identification with objects and perception rather than subjects and aesthetics renders his work as a prescient and radical example of ecological poetry in the Romantic period. Raymond Williams’ “green language” and Timothy Morton’s ambient poetics both cite Clare as an ideal figure for their above theories and evoke Clare as a writer who positions the environment as governing thought rather than thought governing the environment. This thesis especially relates Clare to Morton’s Ecology without Nature, a study of environmental aesthetics that displaces anthropocentricism and logocentrism with object-oriented ontology (OOO) and an immersion into environmental ambience. This thesis is divided into four sections, each structured by a dichotomy with a hegemonic enclosure of subjects and objects on one side and an alternative remedy that Clare gestures his readers towards. Clare’s poems frame the creation and consumption of literature as a direct connection to our immediate surroundings and by identifying with objects, detects this circumambient and sometimes mundane space as active and sublime. Finally, the arche-writing of Jacques Derrida establishes the written word as an environment not dissimilar to forests and fields and establishes Clare’s poems as a way to sense the environment as coded rather than empty. My correspondence between Derrida’s a priori arche-writing with Clare’s poetics indicates Clare’s successfully representation of uncompromised objects in space rather than objects as inextricably linked to logocentrism’s dominating signifiers and anthropocentric rationality

Testing Scalar-Tensor Gravity with Gravitational-Wave Observations of Inspiralling Compact Binaries

Observations of gravitational waves from inspiralling compact binaries using laser-interferometric detectors can provide accurate measures of parameters of the source. They can also constrain alternative gravitation theories. We analyse inspiralling compact %binaries in the context of the scalar-tensor theory of Jordan, Fierz, Brans and Dicke, focussing on the effect on the inspiral of energy lost to dipole gravitational radiation, whose source is the gravitational self-binding energy of the inspiralling bodies. Using a matched-filter analysis we obtain a bound on the coupling constant $\omega_{\rm BD}$ of Brans-Dicke theory. For a neutron-star/black-hole binary, we find that the bound could exceed the current bound of $\omega_{\rm BD}>500$ from solar-system experiments, for sufficiently low-mass systems. For a $0.7 M_\odot$ neutron star and a $3 M_\odot$ black hole we find that a bound $\omega_{\rm BD} \approx 2000$ is achievable. The bound decreases with increasing black-hole mass. For binaries consisting of two neutron stars, the bound is less than 500 unless the stars' masses differ by more than about $0.5 M_\odot$. For two black holes, the behavior of the inspiralling binary is observationally indistinguishable from its behavior in general relativity. These bounds assume reasonable neutron-star equations of state and a detector signal-to-noise ratio of 10.Comment: 10 pages, (3 figures upon request), WUGRAV-94-

The international pulsar timing array project: using pulsars as a gravitational wave detector

The International Pulsar Timing Array project combines observations of pulsars from both Northern and Southern hemisphere observatories with the main aim of detecting ultra-low frequency (~10^-9 to 10^-8 Hz) gravitational waves. Here we introduce the project, review the methods used to search for gravitational waves emitted from coalescing supermassive binary black-hole systems in the centres of merging galaxies and discuss the status of the project.Comment: accepted by Classical and Quantum Gravity. Review talk for the Amaldi8 conference serie

Networking - A Statistical Physics Perspective

Efficient networking has a substantial economic and societal impact in a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption require new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with non-linear large scale systems. This paper aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.Comment: (Review article) 71 pages, 14 figure

Protein coalitions in a core mammalian biochemical network linked by rapidly evolving proteins

<p>Abstract</p> <p>Background</p> <p>Cellular ATP levels are generated by glucose-stimulated mitochondrial metabolism and determine metabolic responses, such as glucose-stimulated insulin secretion (GSIS) from the β-cells of pancreatic islets. We describe an analysis of the evolutionary processes affecting the core enzymes involved in glucose-stimulated insulin secretion in mammals. The proteins involved in this system belong to ancient enzymatic pathways: glycolysis, the TCA cycle and oxidative phosphorylation.</p> <p>Results</p> <p>We identify two sets of proteins, or protein coalitions, in this group of 77 enzymes with distinct evolutionary patterns. Members of the glycolysis, TCA cycle, metabolite transport, pyruvate and NADH shuttles have low rates of protein sequence evolution, as inferred from a human-mouse comparison, and relatively high rates of evolutionary gene duplication. Respiratory chain and glutathione pathway proteins evolve faster, exhibiting lower rates of gene duplication. A small number of proteins in the system evolve significantly faster than co-pathway members and may serve as rapidly evolving adapters, linking groups of co-evolving genes.</p> <p>Conclusions</p> <p>Our results provide insights into the evolution of the involved proteins. We find evidence for two coalitions of proteins and the role of co-adaptation in protein evolution is identified and could be used in future research within a functional context.</p

MALT90: The Millimetre Astronomy Legacy Team 90 GHz Survey

The Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey aims to characterise the physical and chemical evolution of high-mass star-forming clumps. Exploiting the unique broad frequency range and on- the-fly mapping capabilities of the Australia Telescope National Facility Mopra 22 m single-dish telescope∗ , MALT90 has obtained 3′ × 3′ maps toward _2000 dense molecular clumps identified in the ATLASGAL 870 μm Galactic plane survey. The clumps were selected to host the early stages of high-mass star formation and to span the complete range in their evolutionary states (from prestellar, to protostellar, and on to HII regions and photodissociation regions). Because MALT90 mapped 16 lines simultaneously with excellent spatial (38) and spectral (0.11 km s−1) resolution, the data reveal a wealth of information about the clump’s morphologies, chemistry, and kinematics. In this paper we outline the survey strategy, observing mode, data reduction procedure, and highlight some early science results. All MALT90 raw and processed data products are available to the community. With its unprecedented large sample of clumps, MALT90 is the largest survey of its type ever conducted and an excellent resource for identifying interesting candidates for high resolution studies with ALMA

Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships

Global Analysis of Proline-Rich Tandem Repeat Proteins Reveals Broad Phylogenetic Diversity in Plant Secretomes

Cell walls, constructed by precisely choreographed changes in the plant secretome, play critical roles in plant cell physiology and development. Along with structural polysaccharides, secreted proline-rich Tandem Repeat Proteins (TRPs) are important for cell wall function, yet the evolutionary diversity of these structural TRPs remains virtually unexplored. Using a systems-level computational approach to analyze taxonomically diverse plant sequence data, we identified 31 distinct Pro-rich TRP classes targeted for secretion. This analysis expands upon the known phylogenetic diversity of extensins, the most widely studied class of wall structural proteins, and demonstrates that extensins evolved before plant vascularization. Our results also show that most Pro-rich TRP classes have unexpectedly restricted evolutionary distributions, revealing considerable differences in plant secretome signatures that define unexplored diversity

Common Peptides Study of Aminoacyl-tRNA Synthetases

Aminoacyl tRNA synthetases (aaRSs) constitute an essential enzyme super-family, providing fidelity of the translation process of mRNA to proteins in living cells. They are common to all kingdoms and are of utmost importance to all organisms. It is thus of great interest to understand the evolutionary relationships among them and underline signature motifs defining their common domains.We utilized the Common Peptides (CPs) framework, based on extracted deterministic motifs from all aaRSs, to study family-specific properties. We identified novel aaRS–class related signatures that may supplement the current classification methods and provide a basis for identifying functional regions specific to each aaRS class. We exploited the space spanned by the CPs in order to identify similarities between aaRS families that are not observed using sequence alignment methods, identifying different inter-aaRS associations across different kingdom of life. We explored the evolutionary history of the aaRS families and evolutionary origins of the mitochondrial aaRSs. Lastly, we showed that prevalent CPs significantly overlap known catalytic and binding sites, suggesting that they have meaningful functional roles, as well as identifying a motif shared between aaRSs and a the Biotin-[acetyl-CoA carboxylase] synthetase (birA) enzyme overlapping binding sites in both families.The study presents the multitude of ways to exploit the CP framework in order to extract meaningful patterns from the aaRS super-family. Specific CPs, discovered in this study, may play important roles in the functionality of these enzymes. We explored the evolutionary patterns in each aaRS family and tracked remote evolutionary links between these families