1,249 research outputs found

    Co-Creation as an agonistic practice in the favela of Santa Marta, Rio de Janeiro

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    This paper explores the potential of ‘Co-Creation’ to develop new understandings of neighbourhood disadvantage in collaboration with civil society partners. It argues that there is a growing need for collaborative knowledge production with communities carrying vernacular knowledges previously invalidated by dominant epistemologies. The first part of the paper undertakes a reconceptualization of ‘co-creation’, a term usually associated with citizen involvement in neoliberal contexts, redeveloping it as a ‘critical artistic practice’ (Chantal Mouffe, 2013) in which new ways of imagining the city can be articulated. The second part of the paper examines the practice of Co-Creation as a participatory methodology involving artists, researchers and stakeholders in developing ‘agonistic spaces’ by scrutinizing a five-day workshop conducted in the Rio de Janeiro favela of Santa Marta to explore multiple understandings and meanings of this neighbourhood. Through an analysis of creative workshop activities such as photovoice and mapping exercises, the authors explore the potential of the Co-Creation approach to construct new subjectivities that can help subvert existing configurations of power. The conclusion formulates some recommendations about future strategies to maximise Co-Creation’s potential to engage communities in collaborative knowledge production about their neighbourhoods and bring about positive change.

    Categorical Exclusions for Pavement Preservation Projects

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    Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning

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    A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, contour-based boundary grouping, surface filling-in, spatial attention, and object attention. The model shows how form boundaries can determine regions in which surface filling-in occurs; how surface filling-in interacts with spatial attention to generate a form-fitting distribution of spatial attention, or attentional shroud; how the strongest shroud can inhibit weaker shrouds; and how the winning shroud regulates learning of texture categories, and thus the allocation of object attention. The model can discriminate abutted textures with blurred boundaries and is sensitive to texture boundary attributes like discontinuities in orientation and texture flow curvature as well as to relative orientations of texture elements. The model quantitatively fits a large set of human psychophysical data on orientation-based textures. Object boundar output of the model is compared to computer vision algorithms using a set of human segmented photographic images. The model classifies textures and suppresses noise using a multiple scale oriented filterbank and a distributed Adaptive Resonance Theory (dART) classifier. The matched signal between the bottom-up texture inputs and top-down learned texture categories is utilized by oriented competitive and cooperative grouping processes to generate texture boundaries that control surface filling-in and spatial attention. Topdown modulatory attentional feedback from boundary and surface representations to early filtering stages results in enhanced texture boundaries and more efficient learning of texture within attended surface regions. Surface-based attention also provides a self-supervising training signal for learning new textures. Importance of the surface-based attentional feedback in texture learning and classification is tested using a set of textured images from the Brodatz micro-texture album. Benchmark studies vary from 95.1% to 98.6% with attention, and from 90.6% to 93.2% without attention.Air Force Office of Scientific Research (F49620-01-1-0397, F49620-01-1-0423); National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

    Life and Operating Range Extension of the BPT-4000 Qualification Model Hall Thruster

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    Following completion of the 5,600 hr qualification life test of the BPT-4000 4.5 kW Hall Thruster Propulsion System, NASA and Aerojet have undertaken efforts to extend the qualified operating range and lifetime of the thruster to support a wider range of NASA missions. The system was originally designed for orbit raising and stationkeeping applications on military and commercial geostationary satellites. As such, it was designed to operate over a range of power levels from 3 to 4.5 kW. Studies of robotic exploration applications have shown that the cost savings provided by utilizing commercial technology that can operate over a wider range of power levels provides significant mission benefits. The testing reported on here shows that the 4.5 kW thruster as designed has the capability to operate efficiently down to power levels as low as 1 kW. At the time of writing, the BPT-4000 qualification thruster and cathode have accumulated over 400 hr of operation between 1 to 2 kW with an additional 600 hr currently planned. The thruster has demonstrated no issues with longer duration operation at low power

    Penal arts interventions and hope: outcomes of arts-based projects in prisons and community settings

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    The value of arts-based projects within the criminal justice system is well documented, as research has identified positive outcomes relating to inmates’ behavior and their relationships with others. This article examines the work of the Soft Touch Arts project at HMP Leicester, UK and identifies the importance of hope as a transformative outcome. Interviews with artists in prison and community settings demonstrated the value of engaging in creative and purposeful activity, generating hope which enabled artists to aspire to a better future. This occurred alongside ameliorating the harms of prison and helping artists manage their relationship with probation services

    Penal arts interventions and hope: outcomes of arts-based projects in prisons and community settings

    Get PDF
    The value of arts-based projects within the criminal justice system is well documented, as research has identified positive outcomes relating to inmates’ behavior and their relationships with others. This article examines the work of the Soft Touch Arts project at HMP Leicester, UK and identifies the importance of hope as a transformative outcome. Interviews with artists in prison and community settings demonstrated the value of engaging in creative and purposeful activity, generating hope which enabled artists to aspire to a better future. This occurred alongside ameliorating the harms of prison and helping artists manage their relationship with probation services

    The α–β phase transition in volcanic cristobalite

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    Cristobalite is a common mineral in volcanic ash produced from dome-forming eruptions. Assessment of the respiratory hazard posed by volcanic ash requires understanding the nature of the cristobalite it contains. Volcanic cristobalite contains coupled substitutions of Al3+ and Na+ for Si4+; similar co-substitutions in synthetic cristobalite are known to modify the crystal structure, affecting the stability of the [alpha] and [beta] forms and the observed transition between them. Here, for the first time, the dynamics and energy changes associated with the [alpha]-[beta] phase transition in volcanic cristobalite are investigated using X-ray powder diffraction with simultaneous in situ heating and differential scanning calorimetry. At ambient temperature, volcanic cristobalite exists in the [alpha] form and has a larger cell volume than synthetic [alpha]-cristobalite; as a result, its diffraction pattern sits between ICDD [alpha]- and [beta]-cristobalite library patterns, which could cause ambiguity in phase identification. On heating from ambient temperature, volcanic cristobalite exhibits a lower degree of thermal expansion than synthetic cristobalite, and it also has a lower [alpha]-[beta] transition temperature (~473 K) compared with synthetic cristobalite (upwards of 543 K); these observations are discussed in relation to the presence of Al3+ and Na+ defects. The transition shows a stable and reproducible hysteresis loop with [alpha] and [beta] phases coexisting through the transition, suggesting that discrete crystals in the sample have different transition temperatures

    Synthesis and structural characterization of Zn2+, Cd2+ and Hg2+ complexes with tripyrrolidinophosphine chalcogenides

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    Authors are grateful to the Tunisian Ministry of High Education and Scientific Research for support [grant number: LR99ES14] and to the French Service for Cooperation and Cultural Action (SCAC) in Nouakchott, Mauritania for a scholarship to KE.Six new complexes of zinc(II), cadmium(II) and mercury(II) chlorides with tripyrrolidinophosphine chalcogenides of the types [MCl2(Pyrr3PE)2] (M = Zn, E = S (1) or E = Se (2); M = Cd, E = S (3) or E = Se (4)) and [{HgCl(Pyrr3PE)}2(µ-Cl)2] (E = S (5) or Se (6)) have been prepared in yields of 66-92% by reaction of the ligands with metal chloride in ethanol and characterized by 1H and 31P NMR, IR, elemental analysis, conductivity, and single crystal X-ray diffraction analysis. The results show that the complexes are pseudo-tetrahedral containing coordinated chloride ions. Interestingly, the X-ray studies reveal that while the title ligands produce dinuclear complexes with Hg, their Cd and Zn complexes are mononuclear. The tetrahedral bond angles vary from 85.69(5)° to 126.25(4)° in dinuclear complexes 5 and 6 and from 93.51(3)° to 117.38(3)° in mononuclear species 2-4. The E = S bond lengths are in the range 1.999(9)-2.198(2) Å. The coordination properties of the title ligands are discussed and compared to those obtained for their bulkier counterparts.PostprintPeer reviewe

    Stan: A Probabilistic Programming Language

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    Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the cmdstan package, through R using the rstan package, and through Python using the pystan package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. rstan and pystan also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting
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