446 research outputs found

    Siting prisons, sighting communities: geographies of objection in a planning process

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    This paper reviews the planning process for a Scottish prison located near a former mining village. Analysing the letters of objection submitted by residents offers an opportunity to explore local views about prison and community and to relate these to the unique social and spatial history of the area. The planning process itself structured how residents were able to express themselves and defined what counted as a relevant objection. After deconstructing this process, the paper then restores and uses as a framework for analysis three geographies of objection stripped from local responses to the development proposal: the emotional, temporal, and spatial. Emotional expressions of objection added intensity and gave meaning to claims about the historical decline of the region and also conveyed a deep sense of the proposed building site as a lived space. Particular grounds of oppositionā€”over fear of strangers, the fragility of a local orchid, and the pollution from miningā€”provide an opportunity to explore the complex nature of place meaning and community identity, ultimately leading to a conclusion that the meaning of place is always in flux. The paper argues that Simmelā€™s classic concept of the stranger, as the outsider who comes to stay, offers a useful analytic in understanding how the quality of proximal remoteness that prisons and other unwanted developments constitute participates in a constantly evolving sense of the local

    The triggering of MHD instabilities through photospheric footpoint motions

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    The results of 3D numerical simulations modelling the twisting of a coronal loop due to photospheric vortex motions are presented. The simulations are carried out using an initial purely axial field and an initial equilibrium configuration with twist, . The non-linear and resistive evolutions of the instability are followed. The magnetic field is twisted by the boundary motions into a loop which initially has boundary layers near the photospheric boundaries as has been suggested by previous work. The boundary motions increase the twist in the loop until it becomes unstable. For both cases the boundary twisting triggers the kink instability. In both cases a helical current structure wraps itself around the kinked central current. This current scales linearly with grid resolution indicating current sheet formation. For the cases studied 35-40% of the free magnetic energy is released. This is sufficient to explain the energy released in a compact loop flare

    Real-time detection of content polluters in partially observable Twitter networks

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    9th International Workshop on Modeling Social Media (MSM 2018) Applying Machine Learning and AI for Modeling Social Media.Content polluters, or bots that hijack a conversation for political or advertising purposes are a known problem for event prediction, election forecasting and when distinguishing real news from fake news in social media data. Identifying this type of bot is particularly challenging, with state-of-the-art methods utilising large volumes of network data as features for machine learning models. Such datasets are generally not readily available in typical applications which stream social media data for real-time event prediction. In this work we develop a methodology to detect content polluters in social media datasets that are streamed in real-time. Applying our method to the problem of civil unrest event prediction in Australia, we identify content polluters from individual tweets, without collecting social network or historical data from individual accounts. We identify some peculiar characteristics of these bots in our dataset and propose metrics for identification of such accounts. We then pose some research questions around this type of bot detection, including: how good Twitter is at detecting content polluters and how well state-of-the-art methods perform in detecting bots in our dataset.Mehwish Nasim, Andrew Nguyen, Nick Lothian, Robert Cope, Lewis Mitchel

    Profiling the iron, copper and zinc content in primary neuron and astrocyte cultures by rapid online quantitative size exclusion chromatography-inductively coupled plasma-mass spectrometry

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    Metals often determine the chemical reactivity of the proteins to which they are bound. Each cell in the body tightly maintains a unique metalloproteomic profile, mostly dependent on function. This paper describes an analytical online flow injection quantitative size exclusion chromatography-inductively coupled plasma-mass spectrometry (SEC-ICP-MS) method, which was applied to profiling the metal-binding proteins found in primary cultures of neurons and astrocytes. This method can be conducted using similar amounts of sample to those used for Western blotting (20-150 Ī¼g protein), and has a turnaround time of <15 minutes. Metalloprotein standards for Fe (as ferritin), Cu and Zn (as superoxide dismutase-1) were used to construct multi-point calibration curves for online quantification of metalloproteins by SEC-ICP-MS. Homogenates of primary neuron and astrocyte cultures were analysed by SEC-ICP-MS. Online quantification by external calibration with metalloprotein standards determined the mass of metal eluting from the column relative to time (as pg s-1). Total on-column Fe, Cu and Zn detection limits ranged from 0.825 Ā± 0.005 ng to 13.6 Ā± 0.7 pg. Neurons and astrocytes exhibited distinct metalloprotein profiles, featuring both ubiquitous and unique metalloprotein species. Separation and detection by SEC-ICP-MS allows appraisal of these metalloproteins in their native state, and online quantification was achieved using this relatively simple external calibration process. Ā© 2013 The Royal Society of Chemistry

    Characterization and identification of dityrosine cross-linked peptides using tandem mass spectrometry

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    The use of mass spectrometry coupled with chemical cross-linking of proteins has become a powerful tool for proteins structure and interactions studies. Unlike structural analysis of proteins using chemical reagents specific for lysine or cysteine residues, identification of gas-phase fragmentation patterns of endogenous dityrosine cross-linked peptides have not been investigated. Dityrosine cross-linking in proteins and peptides are clinical markers of oxidative stress, aging, and neurodegenerative diseases including Alzheimerā€™s disease and Parkinsonā€™s disease. In this study, we investigated and characterized the fragmentation pattern of a synthetically prepared dityrosine cross-linked dimer of AĪ²(1ā€“16) using ESI tandem mass spectrometry. We then detailed the fragmentation pattern of dityrosine cross-linked AĪ²(1ā€“16), using collision induced dissociation (CID), higher-energy collision induced dissociation (HCD), electron transfer dissociation (ETD), and electron capture dissociation (ECD). Application of these generic fragmentation rules of dityrosine cross-linked peptides allowed for the identification of dityrosine cross-links in peptides of AĪ² and Ī±-synuclein generated in vitro by enzymatic peroxidation. We report, for the first time, the dityrosine cross-linked residues in human hemoglobin and Ī±-synuclein under oxidative conditions. Together these tools open up the potential for automated analysis of this naturally occurring post-translation modification in neurodegenerative diseases as well as other pathological conditions

    Counterintuitive active directional swimming behaviour by Atlantic salmon during seaward migration in the coastal zone

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    Acknowledgements We thank the Cromarty Firth District Salmon Fishery Board for logistical support and three anonymous referees who improved an earlier draft of this paper. Funding for this work came from Scottish & Southern Energy Renewables. We are grateful for the skills and expertise of Bill Ruck at Moray First Marine along with the crews of Marine Scotland Science vessels who were integral to the successful deployment and recovery of equipment. Some receivers were also made available from the Ocean Tracking Network (OTN) The data underlying this article will be shared on reasonable request to the corresponding author.Peer reviewedPublisher PD

    Is shape in the eye of the beholder? Assessing landmarking error in geometric morphometric analyses on live fish

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    Geometric morphometrics is widely used to quantify morphological variation between biological specimens, but the fundamental influence of operator bias on data reproducibility is rarely considered, particularly in studies using photographs of live animals taken under field conditions. We examined this using four independent operators that applied an identical landmarking scheme to replicate photographs of 291 live Atlantic salmon (Salmo salar L.) from two rivers. Using repeated measures tests, we found significant inter-operator differences in mean body shape, suggesting that the operators introduced a systematic error despite following the same landmarking scheme. No significant differences were detected when the landmarking process was repeated by the same operator on a random subset of photographs. Importantly, in spite of significant operator bias, small but statistically significant morphological differences between fish from the two rivers were found consistently by all operators. Pairwise tests of angles of vectors of shape change showed that these between-river differences in body shape were analogous across operator datasets, suggesting a general reproducibility of findings obtained by geometric morphometric studies. In contrast, merging landmark data when fish from each river are digitised by different operators had a significant impact on downstream analyses, highlighting an intrinsic risk of bias. Overall, we show that, even when significant inter-operator error is introduced during digitisation, following an identical landmarking scheme can identify morphological differences between populations. This study indicates that operators digitising at least a sub-set of all data groups of interest may be an effective way of mitigating inter-operator error and potentially enabling data sharing

    The Flare-energy Distributions Generated by Kink-unstable Ensembles of Zero-net-current Coronal Loops

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    It has been proposed that the million degree temperature of the corona is due to the combined effect of barely-detectable energy releases, so called nanoflares, that occur throughout the solar atmosphere. Alas, the nanoflare density and brightness implied by this hypothesis means that conclusive verification is beyond present observational abilities. Nevertheless, we investigate the plausibility of the nanoflare hypothesis by constructing a magnetohydrodynamic (MHD) model that can derive the energy of a nanoflare from the nature of an ideal kink instability. The set of energy-releasing instabilities is captured by an instability threshold for linear kink modes. Each point on the threshold is associated with a unique energy release and so we can predict a distribution of nanoflare energies. When the linear instability threshold is crossed, the instability enters a nonlinear phase as it is driven by current sheet reconnection. As the ensuing flare erupts and declines, the field transitions to a lower energy state, which is modelled by relaxation theory, i.e., helicity is conserved and the ratio of current to field becomes invariant within the loop. We apply the model so that all the loops within an ensemble achieve instability followed by energy-releasing relaxation. The result is a nanoflare energy distribution. Furthermore, we produce different distributions by varying the loop aspect ratio, the nature of the path to instability taken by each loop and also the level of radial expansion that may accompany loop relaxation. The heating rate obtained is just sufficient for coronal heating. In addition, we also show that kink instability cannot be associated with a critical magnetic twist value for every point along the instability threshold
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